Sensing system and method

ABSTRACT

A sensor system includes a multi-frequency sensor assembly including a single sensor body housing with a sensing region circuit and a sensor reader disposed in the sensor body. The sensor body is configured to be in operational contact with a fluid. The sensing region circuit is configured to generate different electric fields having different frequencies in the fluid. The sensor reader includes one or more processors configured to examine one or more impedance responses of the sensing region circuit at different frequencies and to determine one or more properties of the fluid based on the one or more impedance responses that are examined.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 14/866,320, filed 25 Sep. 2015 (the “'320 application”), whichis a continuation-in-part of U.S. patent application Ser. No.14/421,245, filed on 12 Feb. 2015 (the “'245 application”), which claimsthe benefit of U.S. Provisional Patent Application No. 61/692,230, filedon 22 Aug. 2012 (the “'230 application”).

The '320 application also is a continuation-in-part of U.S. patentapplication Ser. No. 14/585,690, filed on 30 Dec. 2014 (the “'690application”), which claims priority to U.S. Provisional PatentApplication No. 61/987,853, filed on 2 May 2014 (the “'853application”).

The '690 application is a continuation-in-part of the followingapplications: U.S. patent application Ser. No. 11/560,476, filed on 16Nov. 2006 (the “'476 application”), U.S. patent application Ser. No.12/325,653, filed on 1 Dec. 2008 (the “'653 application”), U.S. patentapplication Ser. No. 12/824,436, filed on 28 Jun. 2010 (the “'436application”), U.S. patent application Ser. No. 12/827,623, filed on 30Jun. 2010 (the “'623 application”), U.S. patent application Ser. No.12/977,568, filed on 23 Dec. 2010 (the “'568 application”), U.S. patentapplication Ser. No. 13/331,003, filed on 20 Dec. 2011 (the “'003application”), U.S. patent application Ser. No. 13/484,674, filed on 31May 2012 (the “'674 application”), U.S. patent application Ser. No.13/538,570, filed on 29 Jun. 2012 (the “'570 application”), U.S. patentapplication Ser. No. 13/558,499, filed on 26 Jul. 2012 (the “'499application”), U.S. patent application Ser. No. 13/630,939, filed on 28Sep. 2012 (the “'939 application”), U.S. patent application Ser. No.13/630,954, filed on 28 Sep. 2012 (the “'954 application”), U.S. patentapplication Ser. No. 13/630,587, filed on 28 Sep. 2012 (the “'587application”), U.S. patent application Ser. No. 13/630,739, filed on 28Sep. 2012 (the “'739 application”), U.S. patent application Ser. No.13/729,800, filed on 28 Dec. 2012 (the “'800 application”), U.S. patentapplication Ser. No. 13/729,851, filed on 28 Dec. 2012 (the “'851application”), U.S. patent application Ser. No. 13/838,884, filed on 15Mar. 2013 (the “'884 application”), U.S. patent application Ser. No.14/031,951, filed on 19 Sep. 2013 (the “'951 application”), U.S. patentapplication Ser. No. 14/031,965, filed on 19 Sep. 2013 (the “'965application”), and U.S. patent application Ser. No. 14/532,168, filed on4 Nov. 2014 (the “'168 application”).

The '674 application is a continuation-in-part of U.S. patentapplication Ser. No. 12/424,016, filed on 15 Apr. 2009, and is now U.S.Pat. No. 8,364,419, issued on 29 Jan. 2013 (the “'419 patent”).

All the aforementioned applications and patent are incorporated hereinby reference in their entireties.

FIELD

One or more embodiments of the subject matter described herein generallyrelate to systems and methods for detecting an operative condition of amachine or a component of the machine that has movable parts. One ormore embodiments of the subject matter described herein generally relateto systems and method for detecting an operative condition of a machineor a component of the machine that does not have movable parts and/or anaturally occurring system that has or does not have movable parts. Oneor more embodiments are disclosed that relate to sensing methods andsystems. The sensors, such as resonant sensors, may includeinductor-capacitor-resistor (LCR) sensors that can be used as sensors ortransducers for sensing fluids.

BACKGROUND

Many industrial machines (e.g., locomotives, trucks, earth-movingequipment, windmills, and the like) include elements or assemblies(e.g., mechanical drive trains) that operate within difficultenvironments and/or endure substantial amounts of thermal or torsionalstress as well as shock and vibration. It is often desirable to monitora condition of an element or assembly so that it may be replaced orrepaired before severe and permanent damage is sustained by the machine.Often, fluid lubricants are used to provide lubrication and cooling toincrease performance of the machine and/or to increase the lifetimeoperation of the machine. Lubricants reduce the friction between twoparts that engage each other and may also dissipate heat that isgenerated by the friction between the two parts. In addition tolubricants, fluids include other industrial fluid such as fuels,hydraulic media, drive fluids, power steering fluids, power brakefluids, drilling fluids, oils, insulating fluids, heat transfer fluids,or the like. Such fluids allow efficient and safe operation of machineryin transportation, industrial, locomotive, marine, automotive,construction, medical, and other applications. Fluids also includenaturally occurring fluids such as oils, water, body fluids, biologicalfluids, and the like that occur in natural living and non-livingsystems. As one specific example, speed control from a traction motor orother provider of mechanical power may be accomplished with a gear trainor drive train. Gear trains typically include at least two gears thatengage each other. For instance, teeth of a first gear (e.g., piniongear) may engage teeth of a larger gear at a gear mesh. It is common forthe gears to be lubricated by a lubricant (e.g., oil) to reduce thefriction between the gears and to facilitate the dissipation of heatthat is generated during operation. In order for the gears to besuitably lubricated, a designated amount of lubricant is available foruse by the gears.

A gear train may include a gear case that surrounds one or more parts ofthe gear train. The gear case has a reservoir for holding the lubricant.At least one of the gears may move through the reservoir to lubricatethe gear and consequently the gear mesh. At least one of the gears maybe coupled to a shaft that projects out of the gear case. To preventleakage from the reservoir or the gear case, the interface between theshaft(s) and the gear case is sealed.

The sealed interfaces, however, are often exposed to harsh conditions.For example, gear trains of locomotives are frequently exposed to largedifferences in temperature, humid environments, dry environments,abrasive dirt or grime, and/or challenging vibratory states. Theseconditions may cause a failure in the sealed interface thereby resultingin leakage of the lubricant. When an insufficient supply of lubricant isavailable for the gears, the machine may be susceptible to gear train orrolling element bearing damage that results in a locked axle condition.In the case of locomotives, locked axles may require the locomotive tobe removed from service and sent to a facility for repair. Both theremoval and repair of the locomotive may be time-consuming and costly.Furthermore, the lost productivity of the locomotive is also costly.

In addition to having a sufficient amount of lubricant, it is alsodesirable for the lubricant to have a sufficient quality duringoperation. For example, lubricants in a reservoir can becomecontaminated by water, metallic particles, and non-metallic particles.Contaminated fluids may lead to damaged parts or a decreased performanceof the machine. In addition, the lubricant may age due to repetitivethermal and viscous cycles resulting in the loss of fluid propertiessuch as viscosity.

Conventional methods of inspecting fluids of a machine include visualinspection of the fluid (e.g., dipsticks) or a sensor that is directlywired to a system. These methods may not be practical and/or may havelimited capabilities. For example, due to the configuration of somemachines, it may be difficult to visually inspect the fluid. Also,hardwired sensors may not be suitable for machines that frequently moveand/or are exposed to harsh conditions.

In addition to detecting the quantity and/or the quality of a liquidused by a machine, it may be desirable to obtain other informationregarding an operative condition of a machine. For example, when anindustrial machine is operating properly, the machine may have known orexpected vibratory states. When a part of the machine is damaged orotherwise not operating properly, however, the vibrations of the machinemay change. Therefore, it may be desirable to detect the vibrations ofcertain elements in a machine to monitor a health of the elements, othercomponents of the machine, or the machine overall.

Robust sensing of fluids may be useful in mobile and stationaryequipment applications. As one example, if the equipment is a vehicleengine and the fluid is engine oil, then knowledge about oil health maybe used to help reduce or prevent unexpected downtime, provide savingsfrom unnecessary oil replacement, and improve service intervalsscheduling in vehicles such as locomotives, heavy and light duty trucks;mining, construction, and agriculture vehicles. Other examples ofstationary equipment applications may include wind turbines and gensets.Further, knowledge about engine oil health may prevent or reduce thetotal life cost of passenger cars, improve control of service intervals,and extend the life of engine.

Standard (classic) impedance spectroscopy is a technique that isemployed to characterize examples of material performance. In classicimpedance spectroscopy, a material may be positioned between electrodesand probed over a wide frequency range (from a fraction of Hz to tens ofGHz) to extract the fundamental information about dielectric propertiesof the material. Standard impedance spectroscopy may be limited due toits low sensitivity in reported measurement configurations andprohibitively long acquisition times over the broad frequency range.

It may be desirable to have systems and methods that differ from thosesystems and methods that are currently available.

BRIEF DESCRIPTION

In accordance with an embodiment, a system (e.g., a monitoring orsensing system) is provided that includes a sensor configured to bedisposed within a reservoir of a machine having moving parts that arelubricated by a liquid in the reservoir. The sensor is configured toobtain a measurement of the liquid that is representative of at leastone of quantities or qualities of the liquid in the reservoir related toexternal contaminants and oil aging. The system may also include adevice body operably coupled to the sensor. The device body has aprocessing unit that is operably coupled to the sensor and configured togenerate first data signals representative of the measurement of theliquid. The device body also includes a transmitter that is configuredto wirelessly communicate the first data signals to a remote reader. Areader also may be referred to as a sensor reader.

In an embodiment, a system (e.g., a monitoring or sensing system) isprovided that includes a sensor that is configured to be engaged to amechanical element of a drive train to obtain a measurement of avibratory state of the mechanical element. The measurement isrepresentative of an operative condition of the drive train. The systemincludes a device body that has a processing unit operably coupled tothe sensor. The processing unit is configured to generate first datasignals representative of the measurement. The device body also includesa transmitter that is configured to wirelessly communicate the firstdata signals to a remote reader.

In an embodiment, a method (e.g., a method for monitoring an operativecondition of a machine) includes receiving data signals from a wirelessdevice of a machine having a drive train. The wireless device includes adevice body directly coupled to the drive train. The device bodyincludes a transmitter for wirelessly transmitting the data signals. Thedata signals may be based on a measurement of an operative condition ofthe drive train and its lubricating oil condition determined by amultivariable sensor for monitoring external contaminants and oil aging.The method also includes, responsive to determining that the drive trainis operating improperly, generating signals to schedule at least one ofmaintenance of the drive train or replacement of an element of the drivetrain.

In an embodiment, a system (e.g., a monitoring or sensing system)includes a signal-processing module that is configured to receive datasignals from a wireless device of a machine having a drive train. Thedata signals are based on a measurement of an operative condition of thedrive train. The signal-processing module is configured to determine,based on the dynamic data signals provided by at least two identicalsensors, whether the drive train is operating improperly. Optionally,the system also includes a planning module that is configured togenerate an operating plan that is based on the operative condition.

One embodiment of the disclosure provides a system for analyzing fluid.The system may include a sensor. The sensor may include a resonantinductor-capacitor-resistor (LCR) circuit, a sensing region thatincludes at least a portion of the LCR circuit, a controller coupled tothe sensing region. The sensing region may be placed in operationalcontact with a fluid of interest. The controller may receive anelectrical signal from the sensor. The signal may represent resonantimpedance spectra of the sensing region during operational contact withthe fluid over a measured spectral frequency range. The signal may beused to analyze the resonant impedance spectra, and to determine one ormore properties of the fluid such as external contaminants of the fluidand fluid aging based on the analyzed resonant impedance spectra.

In one embodiment, a method includes exciting a sensor in contact with afluid. The sensor may include an LCR resonant circuit to operate at oneor more frequencies in a frequency range of analysis. A signal may bereceived from the sensor across the frequency range of analysis. Thesignal includes information about a sensor in contact with the fluid.One or more properties of the fluid may be determined based at least inpart on the resonant impedance spectra.

A system is provided in one embodiment that includes a resonant sensorand a controller. The sensor can sense a complex permittivity of a fluidacross a broad dispersion range of external contaminants of the fluidand across a broad dispersion range of fluid aging compounds. Thecontroller may be coupled to the sensor and can receive an electricalsignal from the sensor. The signal may represent at least two resonantimpedance spectra of the fluid over a measured spectral frequency range.The controller may determine a complex permittivity of the fluid basedat least in part on the resonant impedance spectra.

In an embodiment, a system includes a sensor and a device body. Thesensor has a sensing region including multiple electrode structures andat least one resonant inductor-capacitor-resistor (LCR) circuit. Eachelectrode structure includes at least two electrodes. The sensing regionis configured to be placed in operational contact with an industrialfluid of interest. The at least one resonant LCR circuit is electricallyconnected to the electrode structures and configured to generate anelectrical stimulus having a spectral frequency range. The electricalstimulus is applied to the industrial fluid via the electrodestructures. The device body is operably coupled to the sensor. Thedevice body includes one or more processors configured to receive anelectrical signal from the sensor that is representative of a resonantimpedance spectral response of the sensing region in operational contactwith the industrial fluid responsive to the electrical stimulus beingapplied to the industrial fluid. The one or more processors areconfigured to analyze the resonant impedance spectral response anddetermine both a concentration of an external contaminant in theindustrial fluid and an aging level of the industrial fluid based on theresonant impedance spectral response that is analyzed.

In another embodiment, a method includes applying an electrical stimulusto an industrial fluid using a sensor. The sensor includes at least oneresonant inductor-capacitor-resistor (LCR) circuit configured togenerate the electrical stimulus. The electrical stimulus is applied tothe industrial fluid via multiple electrode structures at a sensingregion of the sensor in operational contact with the industrial fluid.The method includes receiving an electrical signal from the sensorrepresentative of a resonant impedance spectral response of the sensingregion in operational contact with the industrial fluid responsive tothe electrical stimulus being applied to the industrial fluid. Themethod also includes analyzing, using one or more processors, theresonant impedance spectral response to determine both a concentrationof an external contaminant in the industrial fluid and an aging level ofthe industrial fluid based on the resonant impedance spectral responsethat is analyzed.

In another embodiment, a system for monitoring a condition of anindustrial site includes a sensor with at least two sufficientlynon-correlated output signals representative of a response of the sensorto an industrial fluid at the industrial site. The system also includesa device body operably coupled to the sensor. The device body includesone or more processors configured to receive the output signals from thesensor and analyze the output signals to determine both a concentrationof an external contaminant in the industrial fluid and an aging level ofthe industrial fluid based on the output signals.

While multiple embodiments are disclosed, still other embodiments of thedescribed subject matter will become apparent from the followingDetailed Description, which shows and describes illustrative embodimentsof disclosed inventive subject matter. As will be realized, theinventive subject matter is capable of modifications in variousexamples, all without departing from the spirit and scope of thedescribed subject matter. Accordingly, the drawings and detaileddescription are to be regarded as illustrative in nature and notrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of a system in accordance with an embodiment.

FIG. 2 is a side view of a drive train in accordance with an embodiment.

FIG. 3 is a partially exploded view of a gear case that may be used bythe drive train of FIG. 2.

FIG. 4 is a side view of a capacitive-type sensor in accordance with anembodiment.

FIG. 5 is a schematic view of a magnetic float/reed switch sensor inaccordance with an embodiment.

FIG. 6 is a schematic view of an accelerometer in accordance with anembodiment.

FIG. 7 is a schematic diagram of a wireless device formed in accordancewith an embodiment.

FIG. 8 is a schematic diagram of a wireless device formed in accordancewith an embodiment.

FIG. 9 is a cross-section of a portion of a wireless device utilizingthe sensor of FIG. 4 in accordance with an embodiment.

FIG. 10 is a cross-section of a portion of a wireless device utilizingthe sensor of FIG. 4 in accordance with an embodiment.

FIG. 11 is a cross-section of a wireless device utilizing the sensor ofFIG. 5 in accordance with an embodiment.

FIG. 12 is a cross-section of a portion of a wireless device formed inaccordance with an embodiment.

FIG. 13 is a front view of the wireless device of FIG. 12.

FIG. 14 is a schematic view of a locomotive and illustrates a pluralityof components of the locomotive in accordance with an embodiment.

FIG. 15 illustrates a system in accordance with an embodiment forobtaining data signals from one or more wireless devices.

FIG. 16 is a flowchart illustrating a method in accordance with anembodiment.

FIG. 17 is a block diagram of a system for assessing fluid according toan embodiment of the disclosure.

FIG. 18 is a schematic view of a resonant sensor according to anembodiment of the disclosure.

FIG. 19 is a schematic view of a portion of one example sensor systememploying a sensor assembly configured for sensing of a fluid using aplurality of frequencies, in accordance with embodiments of the presentdisclosure.

FIG. 20 is one example of an equivalent circuit of the resonant sensoraccording to an embodiment of the disclosure.

FIG. 21 is one example of an adapted radio frequency identification(RFID) tag for resonant sensing in which the sensing region constitutesa whole or a portion of the resonant antenna according to an embodimentof the disclosure.

FIG. 22 is one example of an adapted RFID tag for resonant sensing inwhich the sensing region is in galvanic contact with the antenna andmemory chip according to an embodiment of the disclosure.

FIG. 23 is a graph of measured resonant impedance parameters of anembodiment of the resonant sensor, in accordance with embodiments of thepresent technique.

FIG. 24 is one example of a resonant sensor in which the sensing regionis arranged parallel to the sensor axis insertion into the measuredfluid, and therefore, perpendicular to the insertion port of the sensoraccording to an embodiment of the disclosure.

FIG. 25 is one example of a resonant sensor in which the sensing regionis arranged perpendicular to the sensor axis insertion into the measuredfluid, and therefore, parallel to the insertion port of the sensoraccording to an embodiment of the disclosure.

FIG. 26 is one example of sensing of fluid properties with a sensor in afluid reservoir when the sensor is incorporated into the reservoir withthe sensing region of the sensor exposed to the fluid and the sensorreader located near the sensor and connected to the sensor with a cableaccording to an embodiment of the disclosure.

FIG. 27 is one example of sensing of fluid properties with a sensor in afluid reservoir when the sensor is incorporated into the reservoir withthe sensing region of the sensor exposed to the fluid and the sensorreader directly connected to the sensor according to an embodiment ofthe disclosure.

FIGS. 28A-C are graphs depicting measurements related to the sensorreader according to one embodiment.

FIG. 29 is a flow diagram of fluid assessment according to an embodimentof the disclosure.

FIG. 30 is a plot of a resonant impedance data for detection of engineoil, water, and fuel with a highlighted water leak.

FIG. 31 is a plot of a resonant impedance data for detection of engineoil, water, and fuel with a highlighted fuel leak.

FIG. 32 is a principal components analysis of resonant impedancespectral parameters.

FIG. 33 is a correlation plot between the actual (measured) andpredicted concentrations of water in water/fuel/oil mixtures using asingle resonant sensor.

FIG. 34 is a correlation plot between the actual (measured) andpredicted concentrations of fuel in water/fuel/oil mixtures using asingle resonant sensor.

FIG. 35 is a plot of a spectral parameter showing resolution of aresonant sensor to distinguish between hexane and toluene.

FIG. 36 is a plot of a spectral parameter showing resolution of wateraddition into dioxane.

FIG. 37 is a plot of the real part of resonant impedance spectra aftersoot and water addition.

FIG. 38 is a plot of the imaginary part of resonant impedance spectraafter soot and water addition.

FIG. 39 depicts the PCA scores plot of PC1 vs. PC2 upon exposure ofsensor to five solutions and performing resonance impedancemeasurements.

FIG. 40 displays a plot of four resonant spectral profiles from a singlesensor for uncontaminated dioxane.

FIG. 41 displays a plot of resonant spectral profiles from a singlesensor upon addition of water into the dioxane.

FIG. 42 is plot of effects of sensor design on sensitivity of Fpmeasurements.

FIG. 43 displays effects of sensor design on sensitivity of Zpmeasurements.

FIG. 44 is plot of results of measurements of water in oil with twomultivariable resonant sensors.

FIG. 45 is a scores plot of a developed PCA model of responses of theresonant sensor to additions of water at different temperatures, showingdifferent response directions.

FIG. 46 is plot of results of multivariate linear regression model usingpartial least squares technique to quantify water concentrations in oilusing responses of the single sensor.

FIG. 47 is a plot of the actual (measured) concentrations of water inoil over time at three temperatures (solid line) and predictedconcentrations (open circles).

FIG. 48 is a plot of prediction error between actual and predictedconcentrations of water in oil over time at three temperatures.

FIG. 49 is a plot of correlation between actual (measured) and predictedconcentrations of water in oil at three temperatures.

FIG. 50 is a plot of the actual (measured) concentrations of water inoil over time at three temperatures (solid line) and predictedconcentrations (open circles) using responses of a multivariableresonant sensor and oil temperature sensor.

FIG. 51 is a plot of prediction error between actual and predictedconcentrations of water in oil over time at three temperatures usingresponses of a multivariable resonant sensor and oil temperature sensor.

FIG. 52 is a plot of correlation between actual (measured) and predictedconcentrations of water in oil at three temperatures using responses ofa multivariable resonant sensor and oil temperature sensor.

FIG. 53 is a response of a reference capacitance sensor to water leaksinto engine oil at levels of 25, 25, 50, 100, 200, 500, and 1000 ppmeach. Inset shows response to initial water leaks.

FIG. 54 is a response of a developed resonant sensor to water leaks intoengine oil at levels of 25, 25, 50, 100, 200, 500, and 1000 ppm each.Inset shows response to initial water leaks.

FIG. 55 shows operation of the developed resonant sensor in a singlecylinder locomotive engine.

FIG. 56 shows correlation between response of the developed resonantsensor in a single cylinder locomotive engine and the temperature ofoil.

FIG. 57 is a schematic of dynamic signatures of leaks in typicalcomponents in an internal combustion engine.

FIG. 58 is a schematic diagram of a sensing system that includes asensor and a device body.

FIG. 59 depicts responses of a developed resonant sensor to water leaksinto engine oil at levels of 25 ppm, 25 ppm, and 50 ppm each.

FIG. 60 depicts the response of a reference capacitance sensor to waterleaks into engine oil at levels of 25 ppm, 25 ppm, and 50 ppm each.

FIG. 61 shows the response of a multivariable resonant sensor to waterleaks into engine oil responsive to the 50 ppm steps.

FIG. 62 depicts the response of a control tuning fork sensor to waterleaks into engine oil at 50 ppm steps.

FIG. 63 is a plot depicting raw responses of resonance parameters of aresonant impedance spectra measured by the multivariable resonantsensor.

FIG. 64 shows the results of predicted versus actual concentrations forindividual different levels of aging.

FIG. 65 shows a correlation plot between the actual and predicted waterconcentrations for three levels of oil aging (e.g., beginning of arecommended oil life, middle of the recommended oil life, or end of therecommended oil life).

FIG. 66 is a correlation plot between actual and predicted oil agingusing the multivariable resonant sensor.

FIG. 67 depicts raw responses of a conventional capacitance sensor towater additions into differently aged oil samples.

FIG. 68 plots results of predicted vs. actual concentrations of waterconcentrations for individual different levels of aging measured with aconventional capacitance sensor.

FIG. 69 depicts raw responses of (A) F_(p), F₁, F₂ and (B) Z_(p), Z₁, Z₂of the multivariable resonant sensor to water additions into differentlyaged oil samples.

FIGS. 70A-C depict raw dielectric constant, density, and viscosityoutputs, respectively, of a tuning fork sensor.

FIG. 71 shows the results of predicted and actual concentrations ofwater leaks into oil for the multivariable resonant sensor at differentoil aging levels.

FIG. 72 shows the results of predicted and actual concentrations ofwater leaks into oil for the conventional tuning fork sensor atdifferent oil aging levels.

FIGS. 73A-B depict an application of the multiresonant sensor system forthe correction for oil aging that shows one example of the selection ofoperating frequencies of the multiresonant sensor system across thespectral dispersion of locomotive oil.

FIGS. 74A-B depict the real and the imaginary portions of the complexpermittivity of the employed model automotive oil 10W-30 with threelevels of aging such as 0, 50, and 100%.

FIGS. 75A-B show the results of triplicate runs with for the enginewarm-up, baseline (no added water), and water additions of 1000, 3000,and 5000 ppm, and the correlation between the sensor response and addedwater concentration, respectively.

FIGS. 76A-B show responses of an installed multivariable resonant sensorand a tuning fork sensor, respectively, upon testing of engine oil ofthe turboshaft helicopter with an added 5000 ppm of water and observingdynamic response patterns.

FIG. 77 illustrates results of predicted water concentrations versusactual water concentrations in different types of oils using a singletransfer function.

FIG. 78 depicts the Zp and Fp responses of a resonant metal oxidesensor, where Zp is resistance change of the sensor and Fp is frequencypeak position of the sensor.

FIG. 79 is a flow chart representative of a method for determiningmultiple properties of an industrial fluid.

FIG. 80 illustrates another embodiment of a sensor assembly.

FIG. 81 illustrates a circuit diagram of one embodiment of the sensorassembly shown in FIG. 80.

FIG. 82 illustrates a circuit diagram of the sensor assembly shown inFIG. 80 in an embodiment where the resonance of the sensor assembly maybe controlled.

FIG. 83 illustrates operation of the sensor assembly at severaldifferent non-resonant frequencies according to one example.

FIG. 84 illustrates operation of the sensor assembly at severaldifferent resonant frequencies according to one example.

FIG. 85 illustrates measured capacitances for different levels of acontaminant in a fluid under examination according to one example.

FIG. 86 illustrates measured resistances for different levels of thecontaminant in the fluid under examination according to the example ofFIG. 85.

FIG. 87 depicts an example of sensor response Zre as a function ofexperimental time at three frequencies such as 10 kHz, 35 kHz, and 100kHz.

FIG. 88 depicts a scores plot of a developed PCA model based on thesensor response results presented in FIG. 87.

FIG. 89 depicts an example of sensor responses Zre (the real part ofimpedance), Zim (the imaginary part of impedance), Cp (equivalent sensorcapacitance), and Rp (equivalent sensor resistance), all measured at asingle frequency of 100 kHz and using the sensor assembly and sensorreader described in relation to FIG. 87.

FIG. 90 illustrates plots of the first four principal components (PCs)of the developed PCA model as a function of experimental time duringexposures to vapors that show the distinct recognition pattern up to PC4between four model vapors at their four concentration levels.

FIG. 91 depicts results of dynamic measurements of a solution with asensor assembly over time when the changes in the solution propertieswere measured using resonant impedance (two lines and an arrow 1illustrating response direction for the lowest frequency resonator) andconventional impedance (two lines and an arrow 2 illustrating responsedirection).

FIG. 92 depicts results of dynamic measurements of a solution over timewhen the changes in the solution properties were measured using resonantimpedance (two lines and an arrow 1 illustrating response direction forthe lowest frequency resonator) and conventional impedance (two linesand an arrow 2 illustrating response direction).

FIG. 93 illustrates capacitance response and resistance response of thesensor assembly under examination of a fluid such as vapors as measuredby the sensor assembly in accordance with one example.

DETAILED DESCRIPTION

Embodiments described herein include various systems, assemblies,devices, apparatuses, and methods that may be used in a connection withobtaining one or more measurements of a machine. The measurement(s) maybe representative or indicative of an operative condition of themachine. As used herein, an operative condition of the machine may referto an operative condition of the machine as a whole or an operativecondition of a component (e.g., element, assembly, or sub-system) of themachine. As used herein, the operative condition of a machine can relateto a present state or ability of the component and/or a future state orability of the machine to perform one or more operations. For example,the measurement or operative condition may indicate that the machine ora component of the machine is not functioning in a sufficient manner, isdamaged, is likely to be damaged if it continues to operate in adesignated manner, is not likely to perform appropriately underdesignated circumstances, and/or is likely to cause damage to othercomponents of the machine. Alternatively, the measurement or operativecondition may indicate that the machine or component is operatingnormally or is not damaged.

As one example with respect to locomotives or other rail vehicles, oneor more measurements obtained from a locomotive or other rail vehiclemay indicate that a lubricant in the component (e.g., drive train,gearbox, engine, and the like) is low or has an insufficient quality.Embodiments set forth herein may generate an operating plan that isbased on the measurement(s). For instance, the operating plan mayinclude instructions to disable an axle or to limit tractive and/orbraking efforts of the axle. The operating plan may indicate whichelement of the gearbox should be replaced and/or how the machine is tobe operated until the gearbox is replaced. Such operating plans aredescribed in greater detail below.

The measurement may be one of a plurality of measurements that areanalyzed according to embodiments described herein. For instance,embodiments may comprise analyzing multiple measurements that wereobtained at different times from a single sensor to determine anoperative condition of the machine. By way of example, a series ofmeasurements from a single sensor in a gear case may indicate that alubricant level has substantially changed and, thus, the gear case isleaking. Embodiments may also comprise analyzing measurements from aplurality of sensors of the same type. For example, machines may includemultiple gearboxes. Vibration measurements from the gearboxes mayindicate that one of the gearboxes is operating differently than theothers and, thus, may be damaged or in need of maintenance. Embodimentsmay also comprise analyzing different types of measurements to determinean operative condition of the machine. For example, the vibrationmeasurements may be analyzed in light of the speed at which the gearsare driven and/or current environmental conditions. Additionalmeasurements or factors are set forth below.

The measurements may be wirelessly transmitted from a device to areader, which may also be referred to as a receiver. For example, radiowaves representative of the measurement(s) may be transmitted from atransmitter (e.g., antenna) of the wireless device to a remote reader.The reader may be a handheld reader (e.g., capable of being carried in asingle hand by a technician) or an otherwise movable reader. In someembodiments, the reader may have a fixed position. For example, forembodiments in which the machine is a vehicle, the reader may have astationary position along a designated path that is traversed by thevehicle (e.g., railroad tracks, weighing stations, tollbooths). When avehicle passes the reader, the reader may interrogate one or morewireless devices to obtain measurements. Remote readers may also belocated on-board the vehicle. For example, a locomotive or other railvehicle may have a control system that receives data from multiplesources, including one or more wireless devices that communicate themeasurements to the control system.

The measurement may be detected or obtained by a sensor when the devicehaving the sensor is interrogated by the reader. Alternatively oradditionally, the sensor may obtain data at designated intervals (e.g.,one measurement/hour, one measurement/minute, and the like) and/or whena designated event occurs. For example, measurements may only beobtained after the vehicle has been interrogated or after the vehiclehas remained stationary for a certain amount of time (e.g., ten minutes)or after the vehicle has started to move for a certain amount of time(e.g., one minute). In some embodiments, the wireless device includes astorage unit (e.g., memory) where multiple measurements may be stored orlogged. The wireless devices may also include a power source that isintegral to the device. Examples of electrical power sources includebatteries and energy harvesting devices. Energy harvesting devicesconvert energy in the surrounding environment, such as kinetic energy(e.g., vibrations), thermal energy, and electromagnetic energy. Inparticular embodiments, the wireless devices may include or be coupledto a vibratory energy harvesting device that converts kinetic energyinto electrical energy.

The foregoing description of certain embodiments of the presentinventive subject matter will be better understood when read inconjunction with the appended drawings. To the extent that the figuresillustrate diagrams of the functional blocks of various embodiments, thefunctional blocks are not necessarily indicative of the division betweenhardware and circuit. Thus, for example, one or more of the functionalblocks (for example, controllers or memories) may be implemented in asingle piece of hardware (for example, a general purpose signalprocessor, microcontroller, random access memory, hard disk, and thelike). Similarly, the programs may be stand-alone programs, may beincorporated as subroutines in an operating system, may be functions inan installed software package, and the like. The various embodiments arenot limited to the arrangements and instrumentality shown in thedrawings.

FIG. 1 is a schematic diagram of a monitoring or sensing system 100formed in accordance with one embodiment. The system 100 is configuredto obtain one or more measurements that are representative of anoperative condition of a machine 102 or a component of the machine 102(e.g., element, assembly, or sub-system of the machine 102). By way ofexample only, the machine 102 may be a motive machine or vehicle, suchas an off-highway vehicle (e.g., vehicles that are not designed orallowed by law or regulation to travel on public roads, highways, andthe like). Off-highway vehicles include locomotives, mining vehicles,construction equipment, agricultural equipment, industrial equipment,marine vessels, and the like. In some cases, the vehicle may be part ofa vehicle consist in which multiple vehicles are linked directly orindirectly to one another in a common vehicle system (e.g., train). Insome embodiments, the machine is an automobile. In other embodiments,the machine is not configured to travel. For example, the machine may bea windmill or a power-generating turbine or a transformer.

The operative condition may relate to a health or status of a designatedcomponent of the machine. Non-limiting examples of such componentsinclude a gearbox, a gear case, an air compressor, a turbo-charger, or adrive train. The measurement may be analyzed to determine, for example,that a component is damaged, is operating improperly (e.g.,insufficiently or not at all), and/or is operating in a manner that willlead to or cause greater damage to the component or other component ofthe machine 102.

In particular embodiments, the operative condition is determined basedon an amount or quality of liquid used by the machine 102 and/or avibratory state of the machine 102. For instance, in some embodiments,the component may be a gear case that has a reservoir for storing alubricant liquid. A low level or quantity of the liquid in the reservoirmay indicate that the gear case is damaged. In particular, a low levelor quantity may indicate that the gear case is leaking the liquid. Inother embodiments, a component may have a particular vibratory state(s)when the component is operating properly. For example, a mechanicalelement may be configured to oscillate in a known or expected mannerduring operation. However, if the mechanical element is damaged oroperating improperly, the mechanical element may have a differentvibratory state.

As shown, the system 100 may include a wireless device 104 that isconfigured to wirelessly communicate data signals to a remote reader106. The data signals may represent the measurement(s) obtained by thewireless device 104. To this end, the wireless device 104 may include asensor 108, a processing unit 110 (also referred to as a controller orcomputer), and a transmitter 112. The sensor 108 is configured tomeasure an operating parameter of the machine 102 and thereby obtain ameasurement. In some embodiments, the sensor 108 includes a detector ortransducer 114 and an activator 116. The activator 116 may be configuredto provide a stimulus (e.g., sound waves, light, electric current, etc.)that causes a response by a component-of-interest or is affected by thecomponent-of-interest. The detector 114 may be configured to detect theresponse that is caused by the stimulus or the affect that thecomponent-of-interest has on the stimulus. For example, the stimulus maybe sound waves that are detected to determine a liquid level (e.g.,sonar). The stimulus may be light signals that are projected by a laserinto a liquid to determine how much of the light signals are absorbed bythe liquid. Another stimulus may be electric current. In otherembodiments, the sensor 108 does not include an activator 116. Instead,the detector 114 may detect sound, vibrations, light, temperature,electrical properties, or other properties that occur in the environmentwithout a stimulus provided by an activator.

The processing unit 110 is operably coupled to the sensor 108. Theprocessing unit 110 is configured to receive measurement signals fromthe sensor 108 and process the measurement signals to provide datasignals. The processing unit 110 may be an analog-to-digital converter(ADC). Alternatively or in addition to the ADC, the processing unit 110may include a logic-based device that transforms the measurement signalsinto data signals. The data signals may then be configured to betransmitted to the reader 106 by the transmitter 112. For example, theprocessing unit 110 may be a computer processor, controller (e.g.,microcontroller) or other logic-based device that performs operationsbased on one or more sets of instructions (e.g., software). Theinstructions on which the processing unit 110 operates may be stored ona tangible and non-transitory (e.g., not a transient signal) computerreadable storage medium, such as a memory. The memory may include one ormore types of memory, such as hard drives, flash drives, RAM, ROM,EEPROM, and the like. Alternatively, one or more of the sets ofinstructions that direct operations of the processing unit 110 may behard-wired into the logic of the processing unit 110, such as by beinghard-wired logic formed in the hardware of the processing unit 110.

The transmitter 112 is operably coupled to the processing unit 110 andis configured to wirelessly communicate the data signals to the reader106. In some embodiments, the transmitter 112 is a transceiver that isconfigured to transmit the data signals and receive other signals, suchas interrogation signals from the reader 106.

In some embodiments, the sensor 108, the processing unit 110, and thetransmitter 112 are localized within and/or attached directly to themachine such that the sensor 108, the processing unit 110, and thetransmitter 112 are proximate to each other and form a single device. Inone embodiment, the sensor 108, processing unit 110, and transmitter 112are located inside a single continuous or contiguous body, such as asingle external housing. The sensor 108, the processing unit 110, andthe transmitter 112 may be in a localized spatial region of the machinethat is separate from a computing system that controls operation of themachine. For example, the processing unit 110 and the transmitter 112may be integrated with the same component such that the processing unit110 and the transmitter 112 have fixed positions with each other. Morespecifically, the processing unit 110 and the transmitter 112 may be atleast partially integrated onto a common component (e.g., circuit board)and/or positioned within a common container or housing that is coupledto the machine. The common container may not be coextensive with themachine and, instead, may be a separate component that is attached to ordisposed within the machine-of-interest. By way of example only, some orall of the components of the processing unit 110 and the transmitter 112may be located within 50 cm of each other, 20 cm of each other, 10 cm ofeach other or, more particularly, within 5 cm of each other.

In some embodiments, the processing unit 110 and the transmitter 112 maybe part of a common radio frequency identification (RFID) unit (e.g.,tag, chip, card, and the like). Optionally, the sensor 108 may also bepart of the common RFID unit. In other cases, the sensor 108 is separatefrom, but operably coupled to, the RFID unit and is only a shortdistance from the RFID unit. For example, the sensor 108 may be locatedwithin 50 cm or less of the RFID unit and communicatively coupled viawires or wireless communication. The RFID unit may be formed inaccordance with RFID technology, which may include integrated circuittechnology. For example, the RFID unit may be an electronic circuit thatis capable of wireless communication. In some instances, the RFID unitmay satisfy one or more established RFID standards and/or guidelines,such as standards and guidelines formed by the InternationalOrganization for Standardization (ISO), the InternationalElectrotechnical Commission (IEC), ASTM International, the DASH7Alliance, EPCglobal, the Financial Services Technology Consortium(FSTC).

In certain embodiments, the wireless device 104 is not physicallyelectrically connected (e.g., not connected by wires or otherconductors) to any of the one or more computers or othercontroller-based units in the machine. For example, in the context oftrains, the wireless device 104 may be partially disposed within areservoir and/or attached to a wall that defines the reservoir and isnot physically electrically connected to the computing system thatcontrols operation of the train. In such embodiments, the data signalsfrom the wireless device 104 may be wirelessly transmitted from thewireless device 104 to, for example, a reader that is on-board oroff-board. More specifically, the data signals may not be transmittedvia wire/cables or other physical electrical connections. In one or moreembodiments, at least portions of the processing unit 110 and thetransmitter 112 may be directly connected to a wall that defines thereservoir (e.g., a wall that bears a pressure of and/or contacts theliquid in the reservoir) and/or to a structure immediately connected tothe wall (e.g., support structure of the reservoir, gear case, or thelike).

Various forms of wireless communication may be transmitted and receivedby the wireless device 104. For example, the transmitter 112 may beconfigured to receive and/or transmit radio signals, optical signals,signals based on sound, or signals based on magnetic or electric fields.In particular embodiments, the transmitter 112 is configured to receiveand/or transmit radio signals in one or more radio frequencies. Thewireless signals may be transmitted along a narrow radio band. In narrowband transmission, a single carrier frequency is used. Alternatively,the wireless signals may be transmitted within a spectrum of radiofrequencies. For example, in spread spectrum transmission, the signalsmay be transmitted over a number of different radio frequencies within aradio band. The data signals may be modulated for transmission inaccordance with any one of a number of modulation standards, such asfrequency-hopping spread spectrum (FHSS), direct-sequence spreadspectrum (DSSS), or chirp spread spectrum (CSS). One wirelesscommunication standard that may be used by embodiments described hereinis IEEE 802.15.4. The IEEE 802.15.4 standard may operate within one ofthree frequency bands: (1) 868.0-868.6 MHz; (2) 902-928 MHz; or (3)2400-2483.5 MHz. A number of channels may be used in each of thefrequency bands. Embodiments may also use frequency bands that areassociated with RFID technology, such as 120-150 kHz, 13.56 MHz, 865-868MHz, 902-028 MHz, 2450-5800 MHz, or 3.1-10 GHz. Ultra wideband (UWB) mayalso be used.

In some embodiments, a transmission range of the data signals and/or thesignals from the reader 106 is about 0-10 meters or from about 0-20meters. In other embodiments, the transmission range may be greater,such as up to 100 meters or more.

Various embodiments may be based on or consistent with RFID technology.For example, the wireless device 104 may be a passive sensor, asemi-passive sensor, or an active sensor. A passive sensor may notinclude a power source. Instead, the power may be based on inductivecoupling or backscatter coupling with the reader. A passive sensor mayoperate over a frequency range from about 1 kHz to about 10 GHz. Asemi-passive sensor may include a power source for only designatedfunctions. For example, a battery and/or an energy harvesting device maybe used to increase the transmission distance. The passive andsemi-passive sensors may be particularly suitable for when the reader ispresent (e.g., within transmission range so that the sensors can bepowered by the reader). An active sensor may include a power source forpowering multiple functions (e.g., detection, reception, andtransmission). Active sensors may be used in embodiments in which thereader is configured to only receive data signals and not transmitinterrogation signals.

The reader 106 may be operably connected to a control system 118 havinga signal-processing or diagnostic module 120 and, optionally, a planningmodule 122. Like the processing unit 110, the modules 120, 122 may be acomputer processor, controller (e.g., microcontroller), or otherlogic-based device that performs operations based on one or more sets ofinstructions. The instructions on which the modules 120, 122 operatesmay be stored on a tangible and non-transitory (e.g., not a transientsignal) computer readable storage medium, such as a memory.Alternatively, one or more of the sets of instructions that directoperations of the modules 120, 122 may be hard-wired into the logic ofthe modules 120, 122. The module 120, 122 may be located on separatedevices (e.g., separate processors) or may be located on commonprocessor.

The signal-processing module 120 may be configured to determine, basedon the data signals received by the reader 106, whether the machine 102is operating improperly. The signal-processing module 120 may determinewhether the machine 102 is operating properly or improperly by analyzingthe data signals that are representative of the measurements. Forexample, the signal-processing module 120 may use a look-up table orother databases that provides acceptable ranges of operation. If themeasurement based on the data signals is not within the range, thesignal-processing module 120 may determine that the machine 102 is notoperating properly. In some cases, based on the measurement(s), thesignal-processing module 120 may be able to determine whether aparticular component of the machine 102 is in need of maintenance,repair, or replacement or whether the machine 102 requires an overhaulof a sub-system.

Based on the measurement(s), the signal-processing module 120 mayrequest that an operating plan be generated by the planning module 122.The operating plan may be configured to improve the performance of themachine 102 and/or to limit the performance of the machine 102 toprevent damage or additional damage. The operating plan may includeinstructions for replacing, maintaining, modifying, and/or repairing adesignated component or components of the machine 102.

The operating plan may be based on the operative condition, which is atleast partially a function of the measurement(s) obtained. For instance,if a capacitive measurement indicates that the liquid level is less thansufficient, but a substantial amount remains in the gear case, then theoperating plan may include instructions for refilling the liquid at afirst facility and then resealing the gear case at a second facilitylocated further away. However, if a capacitive measurement indicatesthat the liquid level quickly reduced to little or no measurable amountof liquid, then the operating plan may instruct that the gear case bereplaced at a designated facility.

In the context of a locomotive or other vehicle, the operating plan mayinclude instructions for controlling tractive and/or braking efforts ofthe vehicle. In particular, the operating plan may be partially based onthe measurements of the operative condition of the machine. Theinstructions may be expressed as a function of time and/or distance of atrip along a route. In some embodiments, travel according to theinstructions of the operating plan may cause the vehicle to reduce astress on a component-of-interest of the machine than the componentwould typically sustain during normal operation. For example, theoperating plan may instruct the vehicle to reduce horsepower deliveredto an axle, to intermittently drive the axle, or to disable the axlealtogether. The vehicle may be autonomously controlled according to theoperating plan or the instructions of the operating plan may bepresented to an operator of the vehicle so that the operator canmanually control the vehicle according to the operating plan (alsoreferred to herein as a “coaching mode” of the vehicle).

In some embodiments, the operating plan that is generated when it isdetermined that the machine is operating improperly is a “revised”operating plan that supersedes or replaces another operating plan. Morespecifically, due to the newly acquired measurements, the control systemmay determine that the currently-implemented operating plan should bemodified and, as such, may generate a revised operating plan to replacethe other.

Operating plans may be optimized to achieve designated goals orparameters. As used herein, the term “optimize” (and forms thereof) arenot intended to require maximizing or minimizing a characteristic,parameter, or other object in all embodiments described herein. Instead,“optimize” and its forms may include increasing or decreasing (asappropriate) a characteristic, parameter, or other object toward adesignated or desired amount while also satisfying other conditions. Forexample, optimized stress levels on a component may not be limited to acomplete absence of stress or that the absolute minimum amount ofstress. Rather, optimizing the stress level may mean that the stress iscontrolled, while also satisfying other conditions (e.g., speed limits,trip duration, arrival time). For example, the stress sustained by acomponent may be controlled so that the vehicle may arrive at itsdestination without the component being severely damaged.

The planning module 122 is configured to use at least one of vehicledata, route data (or a route database), part data, or trip data togenerate the operating plan. The vehicle data may include information onthe characteristics of the vehicle. For example, when the vehicle systemis a rail vehicle, the vehicle data may include a number of rail cars,number of locomotives, information relating to an individual locomotiveor a consist of locomotives (e.g., model or type of locomotive, weight,power description, performance of locomotive traction transmission,consumption of engine fuel as a function of output power (or fuelefficiency), cooling characteristics), load of a rail vehicle witheffective drag coefficients, vehicle-handling rules (e.g., tractiveeffort ramp rates, maximum braking effort ramp rates), content of railcars, lower and/or upper limits on power (throttle) settings, etc.

Route data may include information on the route, such as informationrelating to the geography or topography of various segments along theroute (e.g., effective track grade and curvature), speed limits fordesignated segments of a route, maximum cumulative and/or instantaneousemissions for a designated segment of the route, locations ofintersections (e.g., railroad crossings), locations of certain trackfeatures (e.g., crests, sags, curves, and super-elevations), locationsof mileposts, and locations of grade changes, sidings, depot yards, andfuel stations. The route data, where appropriate, may be a function ofdistance or correspond to a designated distance of the route.

Part data may include, for example, historical data or proprietary dataregarding the lifetime operability of a component. The data may includebaseline data for a designated speed and/or load on the machine.Additional factors may be part of the baseline data. For example, if thelubricant has a designated quantity in the gear case, the part data mayinclude data from identical components that operated with anapproximately equal lubricant level. The data may include how long thecomponent is capable of operating at a designated speed.

Trip data may include information relating to a designated mission ortrip, such as start and end times of the trip, start and end locations,route data that pertains to the designated route (e.g., effective trackgrade and curvature as function of milepost, speed limits), uppercumulative and/or instantaneous limits on emissions for the trip, fuelconsumption permitted for the trip, historical trip data (e.g., how muchfuel was used in a previous trip along the designated route), desiredtrip time or duration, crew (user and/or operator) identification, crewshift expiration time, lower and/or upper limits on power (throttle)settings for designated segments, etc. In one embodiment, the planningmodule 122 includes a software application or system such as the TripOptimizer™ system developed by General Electric Company.

FIG. 2 is a side view of a drive train (or final drive) 150 inaccordance with one embodiment. The drive train 150 includes a tractionmotor 152, a first (or pinion) gear 154, a second gear 156, and a baseportion or shell 160 of a gear case 158. A top portion or shell 162 ofthe gear case 158 is shown in FIG. 3. As shown in FIG. 2, the first gear154 and the second gear 156 engage each other at a gear mesh 164. Duringoperation of the drive train 150 the traction motor 152 drives the firstgear 154 by rotating an axle (not shown) coupled to the first gear 154about an axis of rotation 166. The first gear 154 may be rotated, forexample, in a counter-clockwise direction as viewed in FIG. 2. Due tothe engagement at the gear mesh 164, the first gear 154 rotates thesecond gear 156 in a clockwise direction about an axis of rotation 168.The second gear 156 is coupled to an axle (not shown) that rotates withthe second gear 156. The axle of the second gear 156 is coupled towheels (not shown) that are rotated with the axle. The wheels engage asurface (e.g., rails or tracks) to move the machine.

The gear case 158 includes a reservoir 172 that is configured to hold alubricant liquid 180 (e.g., oil). The gear case 158 has a fill or inletport 186 and a drain or outlet port 188. The liquid 180 may be providedto the reservoir 172 through the fill port 186 and drained through thedrain port 188.

As shown in FIG. 2, the second gear 156 has teeth 176 along an edge 174of the second gear 156. When the liquid 180 is held within the gear case158, the liquid 180 may have a fill level 184. FIG. 2 illustrates afirst fill level 184A and a second fill level 184B. The second filllevel 184B is lower than the first fill level 184A. In some embodiments,when the drive train 150 is operating properly, the quantity of theliquid 180 correlates to the first fill level 184A such that the edge174 of the second gear 156 is sufficiently submerged within or bathed bythe liquid 180. However, when the fill level is lowered to, for example,the fill level 184B, the edge 174 and teeth 176 may be insufficientlylubricated. Such circumstances may occur when the gear case 158 has aleak.

FIG. 3 is a partially exploded view of the gear case 158 and illustratesthe base and top portions 160, 162 before the base and top portions 160,162 are coupled to the drive train to surround the first and secondgears 154, 156. As shown, the gear case 158 may include first and secondgear-receiving openings 190, 192 that are sized to receive the first andsecond gears 154, 156 (FIG. 2), respectively. The gear-receivingopenings 190, 192 may be defined by opening edges 193-196 and the baseand top portions 160, 162 may engage each other along case edges 197,198.

When the drive train 150 is fully constructed and operational, theopening edges 193-196 engage the portions of the drive train 150 alongsealable interfaces. The case edges 197, 198 may also be coupled to eachother along a sealable interface. During operation of the drive train150, however, the interfaces may become damaged or worn such that theinterfaces are no longer sufficiently sealed. For example, when thedrive train 150 is part of a locomotive, the opening edges 193-196 orthe case edges 197, 198 may become worn, damaged, or separated such thatthe liquid 180 is permitted to escape the reservoir 172. Accordingly,the amount of liquid 180 may reduce such that the fill level 184 (FIG.2) lowers.

Embodiments described herein may be configured to detect that the amountof liquid 180 has reduced. In addition, due to the wear, damage, orseparation of the base and top portions 160, 162, the gear case 158 (orportions thereof) may exhibit different vibratory characteristics. Forexample, a gear case that is sufficiently sealed with respect to thedrive train 150 and has a sufficient fill level 184 may exhibit a firstvibratory state when the drive train 150 is driven at a first speed.However, a gear case that is insufficiently sealed with respect to thedrive train 150 and/or has an insufficient fill level 184 may exhibit asecond vibratory state that is different than the first vibratory statewhen the drive train 150 is driven at the first speed. Embodimentsdescribed herein may be configured to detect and measure the differentvibratory states. In certain embodiments, a wireless device, such asthose described herein, is at least partially disposed within thereservoir 172 and/or directly attached to a portion of the gear case158. For example, at least a portion of the wireless device 104 may bedirectly secured or affixed to a wall of the gear case 158, such as thewall that defines the reservoir 172. In some embodiments, the wirelessdevice 104 is not physically electrically connected to other componentsof the machine, such as a computing system that controls operation ofthe machine.

In addition to liquid level and vibrations, embodiments may beconfigured to detect other characteristics. For example, othermeasurements may relate to a quality (e.g., degree of contamination) ofthe liquid. Contaminants may include water, metallic particles, and/ornon-metallic particles. Furthermore, embodiments are not limited to thedrive train or a gear case of the drive train. For example, measurementsthat may be obtained for a drive train may also be obtained for aturbo-charger, an air compressor, an engine, and the like. Othercomponents of a machine may also be measured by wireless devicesdescribed herein.

FIGS. 4-6 illustrate sensors 202, 212, 222, respectively. The sensors,which may also be referred to as transducers, may be a portion of thewireless devices described herein. Each of the sensors may be configuredto measure (e.g., detect) a designated property or characteristic in theenvironment proximate to the sensor and provide a signal that isrepresentative of the measured property or characteristic. The signalprovided by the sensor may be the measurement.

Various types of measurements may be obtained by the sensors. Somenon-limiting examples include a capacitance of a liquid, a temperatureof a liquid and/or temperatures of certain parts of a machine, a fluidconduction of a liquid, a dielectric constant of a liquid, a dissipationfactor of a liquid, an impedance of a liquid, a viscosity of a liquid,or vibrations of a mechanical element. A measurement may be directlyobtained (e.g., temperature) by the sensor, or a designated measurementmay be obtained after using information provided by the sensor tocalculate the designated measurement. For example, the viscosity of theliquid may be calculated based on multiple level measurements obtainedby a sensor.

Embodiments may include a single wireless device that is configured tomeasure and communicate only a single type of measurement (e.g.,capacitance). However, in some embodiments, a single wireless device maybe configured to measure and communicate multiple types of measurements(e.g., capacitance of the liquid, temperature of the liquid, temperatureof the sensor, shock and/or vibration of the gear case, etc.). In suchembodiments, the wireless device may have multiple sensors.

The sensor 202 is configured to measure a capacitance of a liquid, suchas a lubricant in a tank (e.g., gear case). The sensor 202 ishereinafter referred to as a capacitive level probe 202. For reference,a cross-section 201 of the level probe 202 is also shown in FIG. 4. Thelevel probe 202 extends lengthwise between a leading end 208 and atrailing end 210. The level probe 202 includes an inner or measurementelectrode 204 and an outer or reference electrode 206. As shown, a space205 exists between the inner and outer electrodes 204, 206. Acapacitance of the material that exists within the space 205, such as acombination of a liquid and gas, may be measured by the level probe 202.In some embodiments, a wall of the tank that holds the liquid may beused as the reference electrode.

The level probe 202 is configured to be immersed into the liquid (e.g.,oil) held by the tank. For example, the leading end 208 may be insertedinto the liquid. As the leading end 208 is submerged, the liquid mayflow into the space 205 thereby changing a ratio of liquid to gas withinthe space 205. As such, the measured capacitance changes as the level ofthe liquid within the space 205 changes. If the liquid is a lubricant,the measured value of capacitance decreases as an amount or level of theliquid decreases. As an amount or level of the liquid increases, themeasured value of capacitance also increases.

The level probe 202 may also be configured to determine a quality of theliquid. More specifically, the level probe 202 may detect an amount orpercentage of contaminations in the liquid based on capacitancemeasurements. For example, contaminant detection may be based on adissipation factor of a dielectric of the liquid. In general, thedissipation factor is a function of an applied frequency, a liquidtemperature, a composition of the liquid (e.g., the desired compositionof the liquid), and contaminants. The dissipation factor may besubstantially independent of the base capacitance or liquid level.

In some cases, movement of the machine may cause a displacement of theliquid which may introduce an error in the measurements. Accordingly, insome embodiments, the level probe 202 is only activated when the machineor component thereof is at rest (e.g., inactive). To this end, anaccelerometer or other inertial type sensor may be part of or operablycoupled to the wireless device that includes the level probe 202. Theaccelerometer may determine that the machine is in an inactive orstationary state such that measurements may be obtained by the levelprobe 202.

As shown in FIG. 5, the sensor 212 includes a body float 214 and a reedswitch 216. The body float 214 includes a cavity 218 that is sized andshaped to receive the reed switch 216. The body float 214 is configuredto float along the reed switch 216 (e.g., vertically) based on a levelof the liquid in the reservoir. The body float 214 includes a permanentmagnet 220, and the reed switch 216 includes a magnetically actuatedswitch or switches (not shown). As the body float 214 moves up and down,the permanent magnet 220 may activate or deactivate the switch (e.g.,close or open a circuit, respectively, in the reed switch 216). Theactivated switch indicates that the body float 214 is at a designatedlevel and, consequently, that the liquid is at a designated level.

As described above, one or more embodiments may also include a sensorthat is an accelerometer. FIG. 6 illustrates one such sensor, which isreferenced as an accelerometer 222. In some embodiments, theaccelerometer 222 is a micro-electro-mechanical system (MEMS) tri-axisaccelerometer. The accelerometer 222 may be used for a variety offunctions. For example, the accelerometer 222 may be coupled to amechanical element, such as a tank, and determine whether the mechanicalelement has remained stationary for a designated amount of time. In someembodiments, other measurements (e.g. liquid level) may be obtained onlyafter it has been determined that the mechanical element has remainedstationary for the designated amount of time.

Alternatively or additionally, the accelerometer 222 may be configuredto detect vibratory states experienced by the mechanical element. Forexample, the accelerometer 222 may be configured to obtain numerousshock and vibrations measurements per second in each of x-, y-, andz-axes. For example, the accelerometer 222 may be able to log hundredsor thousands of data points per second in each of the x-, y-, andz-axes.

FIG. 7 is a schematic diagram of a wireless device 300 formed inaccordance with one embodiment. The wireless device 300 includes sensors301-304, a processing unit 306 (e.g., microprocessor), a transmitter308, an internal clock 310 (e.g., real-time clock crystal), and a memory312 (e.g., non-volatile memory). The wireless device 300 has a devicebody 315, which may include a printed circuit board (PCB) or a die(e.g., semiconductor wafer) in some embodiments. In the illustratedembodiment, the device body 315 includes the sensors 303, 304, theprocessing unit 306, the transmitter 308, the internal clock 310, andthe memory 312. In alternative embodiments, however, the wireless device300 may have multiple bodies (e.g., multiple dies) that are coupled toeach other and/or the components described herein may be separate fromthe device body 315. The sensors 301 and 302 may be operably coupled tothe device body 315 through, for example, wires 316. In otherembodiments, the sensors 301, 302 are wirelessly coupled to the devicebody 315.

The sensor 301 may be a level probe, such as the level probe 202described with respect to FIG. 4. The sensor 301 is configured to beinserted into a liquid (e.g., lubricant) of a machine. The sensor 302may be a thermometer that is configured to obtain a temperature of theliquid. The sensor 303 is an accelerometer, such as the accelerometer222 (FIG. 6), and the sensor 304 is another thermometer that isconfigured to determine a temperature of the device body 315 of thewireless device 300. Each of the sensors 301-304 is communicativelycoupled to the processing unit 306 and configured to communicate signalsto the processing unit 306. The signals may be representative of aproperty or characteristic detected by the sensor.

The processing unit 306 may be configured to store or log data (e.g.,data based on the signals obtained from the sensors) in the memory 312.In some embodiments, the processing unit 306 is configured to query thesensors 301-304 to request measurements from the sensors 301-304. Thequeries may occur at predetermined times or when a designated eventoccurs. For example, the queries may occur once an hour as determined bythe internal clock 310 until, for example, the wireless device 300 isinterrogated by a reader (not shown). At such an event, the processingunit 306 may query the sensors 301-304 for numerous data points. Forexample, the data points may be provided almost continuously afterinterrogation. The processing unit 306 may also receive data from thememory 312. The data received from the sensors 301-304 and/or the memory312 may be transformed into data signals that are communicated by thetransmitter 308 to the reader.

The wireless device 300 may be characterized as an active orsemi-passive device. For example, the wireless device 300 may include apower source 320, such as a battery (e.g., lithium thionyl chloridebattery) and/or kinetic energy harvesting device. The wireless device300 may utilize the power source 320 to increase the transmission rangeof the transmitter 308. In such embodiments, the reader may be locatedtens or hundreds of meters away from the wireless device 300. Inaddition to the transmitter 308, the power source 320 may be used tosupply power to other components of the wireless device 300, such as thesensors 301-304 or the processing unit 306.

FIG. 8 is a schematic diagram of a wireless device 350 formed inaccordance with one embodiment. The wireless device 350 may be a passivedevice such that the wireless device 350 is powered by inductive orbackscatter coupling with the reader (or some other non-internal powersource). As shown, the wireless device 350 includes sensors 351-354, aprocessing unit 356, and a transmitter 358. The wireless device 300 hasa device body 365 that includes, in the illustrated embodiment, thesensors 353, 354, the processing unit 356, and the transmitter 358. Thedevice body 365 may be formed by integrated circuit technology. Forexample, the device body 365 may include one or more printed circuitboards (PCBs). The sensors 351 and 352 may be operably coupled to thedevice body 365 through, for example, wires 366. Similar to the wirelessdevice 300 (FIG. 7), the sensors 351-354 may be a level probe, externalthermometer, an accelerometer, and an internal thermometer,respectively.

In some embodiments, the processing unit 356 executes fewer calculationsor conversions of the signals from the sensors 351-354 than theprocessing unit 306 (FIG. 7). For example, the processing unit 356 maybe an ADC that converts the analog signals from the sensors 351-354 todigital signals. The digital signals may be the data signals that arethen transmitted by the transmitter 358. In the illustrated embodiment,the processing unit 356 may only query the sensors 351-354 after beinginterrogated by a reader (not shown). More specifically, theinterrogation signals from the reader may power the processing unit 356to query the sensors 351-354 and transmit the data signals.

FIG. 9 is a cross-section of a portion of a wireless device 400 attachedto a wall 402 of a tank 401. The tank 401 may be part of a machine, suchas a locomotive or other machines described herein. The tank 401 isconfigured to have a reservoir 410 for holding a liquid (not shown),such as a lubricant. The reservoir 410 is accessed through a fill port404 of the wall 402 that is defined by interior threads 406 of the wall402 as shown in FIG. 9. The fill port 404 provides access from anexterior 408 of the tank 401 to the reservoir 410.

As shown, the wireless device 400 includes a sensor 412, a device body414, and an intermediate cable portion 416 that joins the sensor 412 andthe device body 414. The wireless device 400 also includes a couplingcomponent 418 that is configured to be secured to the device body 414through, for example, fasteners 420 and attached to the wall 402. In theillustrated embodiment, the coupling component 418 includes threads 422that complement and are configured to rotatably engage the threads 406of the wall 402. However, in other embodiments, different methods ofattaching the coupling component 418 to the tank may be used, such aslatches, interference fits (e.g., plugs), and/or adhesives.

To assemble the wireless device 400, the coupling component 418 may berotatably engaged to the wall 402. The sensor 412 and the cable portion416 may be inserted through an opening 424 of the coupling component 418and the fill port 404. As shown, the coupling component 418 has a matingface 428 that faces in a direction away from the wall 402. The cableportion 416 has a mating end 426 that is located in the exterior 408 ofthe tank 401 and may be pressed toward the mating face 428 with a gasket430 located therebetween. The device body 414 has a cable opening 432that receives an end of the cable portion 416. The device body 414 maybe secured to the cable portion 416 and the coupling component 418 usingthe fasteners 420. As shown, the cable portion 416 includes a fillchannel 436 that permits access to the reservoir 410. During operation,the fill channel 436 may be closed with a plug 438 at the mating end 426of the cable portion 416.

The sensor 412 may be similar or identical to the level probe 202described with respect to FIG. 4. For example, a trailing end 440 of thesensor 412 is shown in FIG. 9. The trailing end 440 is coupled to wires442 that communicatively couple the sensor 412 to the device body 414.In other embodiments, the sensor 462 may be similar or identical to thesensor 212 (FIG. 5). The cable portion 416 is configured to surround andprotect the wires 442 from the surrounding environment. As shown, thewires 442 terminate at a contact ring 444 along the device body 414. Thesensor 412 is configured to transmit signals to the device body 414through the wires 442 and the contact ring 444. The device body 414 isconfigured to process and transmit data signals that representmeasurements obtained by the sensor 412. The device body 414 may includean integrated circuit unit 415. Although not shown, the integratedcircuit unit 415 of the device body 414 may have a processing unit,power source, internal clock, additional sensors, and/or a transmitter,such as those described above. In some embodiments, the integratedcircuit component 415 is formed as an RFID unit.

FIG. 10 is a cross-section of a portion of a wireless device 450, whichis also configured to be coupled to a wall 452 of a tank 451. Thewireless device 450 may include similar features as the wireless device400 (FIG. 9). For example, the wireless device 450 includes a sensor462, a device body 464, and an intermediate cable portion 466 that joinsthe sensor 462 and the device body 464. The wireless device 450 alsoincludes a coupling component 468 that is configured to be secureddirectly to the device body 464 and the cable portion 466 throughfasteners 470. In the illustrated embodiment, the coupling component 468is rotatably engaged to the wall 452 in a similar manner as the couplingcomponent 418 (FIG. 9). However, other methods of attaching the couplingcomponent 468 to the wall may be used.

To assemble the wireless device 450, the coupling component 468 may berotatably engaged to the wall 452. The sensor 462 and the cable portion466 may be inserted through the coupling component 416 and a fill port454 of the wall 452. The device body 464 may be encased within a matingend 476 of the cable portion 466. As shown, the coupling component 468has a mating face 478 that faces in a direction away from the wall 452.Accordingly, the cable portion 466 and the device body 464 may besecured to the coupling component 468 using the fasteners 470. A coverbody 480 may then be positioned over the cable portion 466 to hold thedevice body 464 between the cover body 480 and the coupling component468. Unlike the wireless device 400, the cable portion 466 does notinclude a fill channel that permits access to the reservoir.

The sensor 462 may be similar or identical to the level probe 202described with respect to FIG. 4. For example, a trailing end 490 of thesensor 462 is shown in FIG. 10. The trailing end 490 is coupled to wires492 that communicatively couple the sensor 462 to the device body 464.In other embodiments, the sensor 462 may be similar or identical to thesensor 212 (FIG. 5). As shown, the wires 492 terminate at contacts 494,495 that are coupled to the device body 464. The device body 464 mayinclude an integrated circuit component 465, which, in the illustratedembodiment, is a RFID unit. The sensor 462 is configured to transmitsignals to the integrated circuit component 465 through the wires 492.Like the integrated circuit component 415, the integrated circuitcomponent 465 is configured to process and transmit data signals thatrepresent measurements obtained by the sensor 462. The integratedcircuit component 465 may include a processing unit, power source,internal clock, additional sensors, and/or a transmitter, such as thosedescribed above.

FIG. 11 is a cross-section of a portion of a wireless device 500. Thewireless device 500 may be similar to the wireless device 400 (FIG. 9)and the wireless device 450 (FIG. 10). However, as shown in FIG. 11, thewireless device 500 utilizes a sensor 502 that may be similar to oridentical to the sensor 212 (FIG. 5). The wireless device 500 alsoincludes a coupling component 504 that is configured to attach to a wall506 of a tank 508, which is a gear case in the illustrated embodiment.The coupling component 504 may be similar to the coupling componentsdescribed above. For example, the coupling component 504 may rotatablyengage the wall 506.

Also shown, the wireless device 500 includes a device body 530 that isoperably coupled to the sensor 502 through a base support 510 and anintermediate beam 512. The base support 510 is disposed within anopening 514 of the coupling component 504. The beam 512 extends betweenand joins the sensor 502 and the base support 510. The beam 512 may befabricated from, for example, stainless steel and is configured toprovide a passageway 516 for wires 518 that communicatively couple thedevice body 530 and the sensor 502.

The base support 510 includes a mating face 520 that faces away from thetank 508. The mating face 520 has contacts 524, 525 thereon. The contact524 may be a contact pad, and the contact 525 may be a ring contact thatextends around the contact pad. A device body 530 is configured to berotatably engaged to the coupling component 504. The device body 530includes a mounting surface 532 that faces the mating face 520 and hascorresponding contacts that are configured to engage the contacts 524,525. More specifically, when the device body 530 is rotated to engagethe coupling component 504, the mounting surface 532 of the device body530 may advance toward the mating face 520 so that the contacts of thedevice body 530 press against and engage the contacts 524, 525.

Accordingly, the device body 530 may be communicatively coupled to thesensor 502. Similar to the device bodies described above, the devicebody 530 may include an integrated circuit component 515 having aprocessing unit and a transmitter (not shown). Optionally, theintegrated circuit component 515 may also include a memory, an internalclock, and one or more other sensors. The integrated circuit component515 may transform the signals from the sensor 502 (or memory or othersensors) into data signals. The data signals may then be transmitted toa reader (not shown). In some embodiments, the integrated circuitcomponent 515 is formed as an RFID unit.

FIG. 12 is a cross-section and FIG. 13 is a front view, respectively, ofa portion of a wireless device 550. The wireless device 550 may includea sensor (not shown) and a device body 552 that are communicativelycoupled through wires 554. The sensor may be similar to the sensor 202(FIG. 4) or the sensor 212 (FIG. 5). The device body 552 is secured to afaceplate 556 that is coupled to an exterior surface of a tank 560 (FIG.13). FIGS. 12 and 13 illustrate an embodiment in which no electricalcontacts are required along the device body 552 to electrically join thesensor. Instead, wires 554 (FIG. 12) from the sensor may extend throughpotting 562 that mechanically couples the sensor to the tank 560. Likethe wireless device 400 (FIG. 9), the wireless device 550 may permitaccess to a fill port 566 through a plug 568. Although not shown, thedevice body 552 may include an integrated circuit component, such asthose described above, that processes data signals and transmits datasignals. The integrated circuit component may be an RFID unit that isdirectly coupled to one of the wires 554.

FIG. 14 is a schematic view of a locomotive 600 and illustrates aplurality of components of the locomotive 600 that may include one ormore wireless devices, such as the wireless devices described herein.For example, the locomotive 600 may include a plurality of drive trains601 that each has a gear case 602. The locomotive 600 may also includean engine 604, a turbo-charger 606 operably coupled to the engine 604,and an air compressor 608. Each of the components may have one or moreof the wireless devices described herein operably coupled thereto. Forexample, the gear cases 602 and the engine 604 may have at least one ofthe wireless devices 202, 212, 222, 400, 450, 500, or 550 describedabove. In particular, each of the gear cases 602 and the engine 604 mayhave a reservoir that includes a liquid lubricant. The turbo-charger 606and the air compressor 608 may use, for example, an accelerometersimilar to the wireless device 222.

As shown, the locomotive 600 may also include an on-board control system610. The control system 610 can control the tractive efforts and/orbraking efforts of the locomotive 600 and, optionally, other locomotivesthat are directly or indirectly coupled to the locomotive 600.Operations of the control system 610 may be based on inputs receivedfrom an operator of the locomotive and/or remote inputs from, forexample, a control tower, a dispatch facility, or the like. In addition,the control system 610 may receive inputs from various components of thelocomotive 600. In some cases, the inputs may be data signals receivedthrough wireless communication. For example, the wireless devices of thegear cases 602, the engine 604, the turbo-charger 606, and the aircompressor 608 may be configured to wirelessly communicate data signalsto the control system 610. The control system 610 may include a reader612 for receiving the wireless data signals. The control system 610 mayalso include a signal-processing module and a planning module that aresimilar to the signal-processing and planning modules 120, 122 describedin FIG. 1. The planning module may generate operating plans for thelocomotive 600 based on the inputs received.

FIG. 15 illustrates a system 700 in accordance with one embodiment forobtaining data signals from one or more wireless devices. FIG. 16illustrates a flowchart of a method 750 that may be executed orperformed by the system 700. In some embodiments, the locomotive 600(FIG. 14) may also execute or perform the method 750. The system 700 andthe method 750 may employ structures or examples of various embodimentsdiscussed herein. In some embodiments, certain steps of the method 750may be omitted or added, certain steps may be combined, certain stepsmay be performed simultaneously, certain steps may be performedconcurrently, certain steps may be split into multiple steps, certainsteps may be performed in a different order, or certain steps or seriesof steps may be re-performed in an iterative fashion. Likewise, thesystem 700 is not required to include each and every feature of each andevery embodiment described herein.

With respect to FIG. 15, the system 700 includes a vehicle system 702(e.g., train) including a locomotive consist 704. The locomotive consist704 may include at least one locomotive that is linked (directly orindirectly) to one or more rail cars. For example, FIG. 15 shows thelocomotive consist 704 including first and second locomotives 706, 708and a rail car 710. In other embodiments, the vehicle system 702 mayinclude more rail cars 710. Each of the locomotives 706 and 708 mayinclude a plurality of components that are each monitored by one or morewireless devices. For example, each of the locomotives 706, 708 mayinclude an engine, a turbo-charger, an air compressor, and a pluralityof gear cases, such as those described herein.

As shown in FIG. 15, the vehicle system 702 is approaching a designatedreading location 715. The reading location 715 is a maintenance facilityin the illustrated embodiment. However, the reading location 715 may bea variety of other locations that are capable of receiving wireless datasignals from the locomotives. For example, the reading location 715 maybe a depot, fuel station, wayside location, rail yard entry point orexit point, designated sections of the track(s), and the like. Thereading location 715 includes a plurality of readers 716. Each of thereaders 716 is communicatively coupled (e.g., wirelessly or throughcommunication wires) to a control system 720. Alternatively oradditionally, a handheld reader 724 may be carried by an individual andused to receive the data signals. The reader 724 may also communicatedata signals with the control system 720.

The control system 720 may include a signal-processing module and aplanning module, such as the signal-processing and planning modules 120,122 described in FIG. 1. For example, the control system 720 maygenerate operating plans that include instructions for operating thevehicle system 702 and other similar vehicle systems.

The method 750 may include receiving (at 752) data signals from one ormore of the wireless devices of a machine. In the illustratedembodiment, the machine is the vehicle system 702 or one of thelocomotives 704, 706. However, embodiments described herein are notnecessarily limited to locomotives. The machine may have one orcomponents with moving mechanical elements or parts. For example, themachine may have a drive train, engine, air compressor, and/orturbo-charger. The data signals may be representative of a measurementof an operative condition of the component. By way of example themeasurement may be at least one of a vibration measurement, acapacitance of a liquid, a temperature of a liquid, a fluid conductionof a liquid, a dielectric constant of a liquid, an impedance of aliquid, or a viscosity of a liquid. In particular embodiments, themeasurement is representative of a vibratory state of a gear case or ofa liquid condition of a lubricant held in the gear case.

The receiving operation (at 752) may include receiving the data signalsat one or more fixed readers having stationary positions. For example,the readers 716 may have fixed positions with respect to tracks 730. Thereaders 716 may be located at designated distance from the tracks 730 sothat the readers 716 are capable of receiving the data signals. Thereceiving operation (at 752) may also include receiving the data signalsthrough one or more movable readers, such as the handheld reader 724.

In an alternative embodiment, as described above, the receivingoperation (at 752) may occur with an on-board control system, such asthe control system 610 (FIG. 14).

The method 750 also included determining (at 754), based on the datasignals, whether the component of the machine is operating improperly.For example, the control system 720 may analyze the data signals and,optionally, other inputs to determine whether the component is operatingsufficiently. If the component is operating improperly, the method 750also includes generating (at 755) an operating plan that is based on thedata signals. The operating plan may be a new (or revised) operatingplan that is configured to replace a currently-implemented operatingplan. The method 750 may also include at least one of providingmaintenance (at 756) to the component or replacing (at 758) an elementof the component.

In an embodiment, a system (e.g., a monitoring system) is provided thatincludes a sensor configured to be disposed within a reservoir of amachine having moving parts that are lubricated by a liquid in thereservoir. The sensor is configured to obtain a measurement of theliquid that is representative of at least one of a quantity or qualityof the liquid in the reservoir. The system may also include a devicebody operably coupled to the sensor. The device body has a processingunit that is operably coupled to the sensor and configured to generatefirst data signals representative of the measurement of the liquid. Thedevice body also includes a transmitter that is configured to wirelesslycommunicate the first data signals to a remote reader.

In one example, the transmitter is configured to be energized by thereader when the reader interrogates the transmitter.

In one example, the system includes a power source that is configured tosupply power to the transmitter for transmitting the data signals. Thepower source may include, for example, a battery and/or energyharvesting device.

In one example, the sensor is configured to be at least partiallysubmerged in the liquid.

In one example, the measurement is at least one of a capacitance of theliquid, a temperature of the liquid, a fluid conduction of the liquid, adielectric constant of the liquid, an impedance of the liquid, or aviscosity of the liquid.

In one example, the device body is configured to be affixed to a wall ofthe machine in which the wall at least partially defines the reservoir.

In one example, the sensor and the device body collectively form a firstwireless device. The system may also include a second wireless devicethat is configured to obtain and wirelessly communicate second datasignals that are representative of a measurement of a differentreservoir.

In one example, the sensor is configured to be disposed in a gear caseof a locomotive, the gear case having the reservoir.

In one example, the transmitter is included in a radio-frequencyidentification (RFID) element.

In one example, the sensor, the processing unit, and the transmittercollectively form a first wireless device. The system may also include asecond wireless device that is configured to obtain and wirelesslytransmit data signals that are representative of a measurement of adifferent reservoir. The system may include a signal-processing module.The signal-processing module may be configured to determine, based onthe data signals, whether the machine is operating improperly bycomparing the data signals of the first wireless device to the datasignals of the second wireless device.

In one example, the data signals are configured to be transmitted to ahandheld reader. In another example, the data signals are configured tobe transmitted to a fixed reader located along a railway track. In yetanother example, the data signals are configured to be transmitted to anon-board reader located on a locomotive.

In one example, the sensor includes a multi-conductor capacitive sensorconfigured to detect a capacitance of a fluid. The fluid may function asa dielectric, wherein a level of the fluid affects the capacitancedetected. In another example, the sensor includes a body float and aposition transducer configured to detect a position of the body float.The position transducer may include, for example, a reed switch.

In an embodiment, a system (e.g., a monitoring system) is provided thatincludes a sensor that is configured to be engaged to a mechanicalelement of a drive train to obtain a measurement of a vibratory state ofthe mechanical element. The measurement is representative of anoperative condition of the drive train. The system includes a devicebody that has a processing unit operably coupled to the sensor. Theprocessing unit is configured to generate first data signalsrepresentative of the measurement. The device body also includes atransmitter that is configured to wirelessly communicate the first datasignals to a remote reader.

In one example, the system includes a power source configured to supplypower to the transmitter for transmitting the data signals.

In one example, the system includes a memory. The memory is configuredto log a plurality of the measurements obtained at different times. Thetransmitter is configured to transmit data signals that include themeasurements.

In one example, the sensor, the processing unit, and the transmittercollectively form a first wireless device. The system may include asecond wireless device configured to obtain and wirelessly transmit datasignals that are based on a measurement of a different drive train.

In one example, the device body includes a radio-frequencyidentification (RFID) unit. The RFID unit may have the processing unitand the transmitter.

In an embodiment, a method (e.g., a method for monitoring an operativecondition of a machine) includes receiving data signals from a wirelessdevice of a machine having a drive train. The wireless device includes adevice body directly coupled to the drive train. The device bodyincludes a transmitter for wirelessly transmitting the data signals. Thedata signals may be based on a measurement of an operative condition ofthe drive train. The method also includes, responsive to determiningthat the drive train is operating improperly, generating signals toschedule at least one of maintenance of the drive train or replacementof an element of the drive train.

In one example, the measurement is representative of vibratory state ofa gear case or a liquid condition of a lubricant held in the gear case.

In one example, the measurement is at least one of a vibrationmeasurement of a gear case, a capacitance of a lubricant stored by thegear case, a temperature of the lubricant, a fluid conduction of thelubricant, a dielectric constant of the lubricant, impedance of thelubricant, or a viscosity of the lubricant.

In one example, the data signals are received from a plurality ofwireless devices. The data signals are based on a common type ofmeasurement.

In one example, the data signals are received at a handheld reader.

In one example, the machine is a locomotive and the data signals arereceived at a fixed reader located along a railway track.

In one example, the machine is a locomotive and the data signals arereceived at a reader located on-board the locomotive.

In one example, the method also includes operating the machine accordingto a first operating plan and generating a second operating plan that isbased on the operative condition.

In an embodiment, a system (e.g., a monitoring system) includes asignal-processing module that is configured to receive data signals froma wireless device of a machine having a drive train. The data signalsare based on a measurement of an operative condition of the drive train.The signal-processing module is configured to determine, based on thedata signals, whether the drive train is operating improperly.Optionally, the system also includes a planning module that isconfigured to generate an operating plan that is based on the operativecondition.

In another embodiment, a system (e.g., wireless liquid monitoringsystem) comprises a sensor, a processing unit, and a transmitter. Thesensor is configured to be disposed within a reservoir of a machinehaving moving parts that are lubricated by a liquid in the reservoir.The sensor is configured to obtain a measurement of the liquid that isrepresentative of at least one of a quantity or quality of the liquid inthe reservoir. The processing unit is operably coupled to the sensor andconfigured to generate first data signals representative of themeasurement of the liquid. The transmitter is operably coupled to theprocessing unit and configured to wirelessly communicate the first datasignals to a remote reader.

In another embodiment of the system, alternatively or additionally, thetransmitter is an RFID unit, which may be, for example, similar to anRFID tag, chip, card, or label.

In another embodiment of the system, alternatively or additionally, thesystem is configured to be disposed in the machine (and when installedis actually disposed in the machine), which comprises a vehicle or otherpowered system comprising the reservoir, the moving parts, and one ormore computers or other controller-based units (e.g., a vehiclecontroller) other than the processing unit. The system may not bephysically electrically connected (e.g., not connected by wires or otherconductors) to any of the one or more computers or othercontroller-based units in the machine. Thus, the first data signals mayonly wirelessly transmitted from the system to the reader or elsewhere,and are not transmitted via wire/cables or other physical electricalconnections.

In another embodiment of the system, alternatively or additionally, theprocessing unit and transmitter are co-located proximate to one another(e.g., at least partially integrated onto a common circuit board,positioned within a common box/housing that is positioned within themachine—that is, the common box/housing is not coextensive with theouter body/structure of the machine, but is located within the outerbody/structure—and/or some or all of the components of the processingunit and transmitter are located within 10 cm of each other, within 5 cmof each other, etc., for example), and/or at least portions of theprocessing unit and transmitter are directly connected to a wall of thereservoir (e.g., a wall that bears a pressure of and/or contacts theliquid in the reservoir) and/or to a structure immediately connected tosuch a wall (e.g., support structure of the reservoir, gear case, or thelike).

In another embodiment of the system, alternatively or additionally, thetransmitter is configured to wirelessly communicate the first datasignals to the remote reader that comprises: a remote reader locatedwithin the machine (e.g., if the machine is a vehicle, the remote readeris located with the vehicle); a remote reader located on a wayside of aroute of the machine, the machine comprising a vehicle; a portable(handheld, or otherwise able to be carried by a human operator) remotereader.

Additional embodiments are disclosed that relate to sensing methods andsystems. The sensors, such as resonant sensors, may includeinductor-capacitor-resistor (LCR) sensors that can be used as sensors ortransducers for sensing fluids. Provided herein are sensors having apart that is a resonant structure that exhibits resolvable changes inthe presence of a fluid and various components or contaminants in thefluid.

In one embodiment, the sensor may include an inductor-capacitor-resistor(LCR) resonator circuit with a resonance frequency response provided bythe resonant impedance (Z) of this circuit. The sensors as providedherein may be capable of sensing properties of interest in the presenceof variable noise sources and operating over the variable temperatureconditions to provide stable sensor performance over time. Disclosedherein are sensors that include inductor-capacitor-resistor (LCR)resonators, which may function as a sensor or as a transducer. Theresonant impedance spectrum of the sensor may be measured either viainductive coupling between pick up coil and sensor or directly byconnecting to a sensor reader. The electrical response of the sensor maybe translated into the resonant impedance changes of the sensor.

Non-limiting examples of signal changes of an individual sensor mayinclude combined and simultaneous resonant impedance change, inductancechange, resistance change, and capacitance change (referred to herein aselectrical characteristics). Suitable sensors and systems disclosedherein may enhance the ability to measure changes in a fluid, such asengine oil or fuel, by contacting it with the sensor between theelectrodes that constitute a resonant circuit of the sensor. Theresonant circuit of the sensor may be an electrical resonant circuit.Other resonant circuits may include a mechanical resonator, where achange of viscosity and/or density of the fluid cause a response of themechanical resonators.

Suitable mechanical resonators may include tuning fork resonators,thickness shear mode resonators, quartz crystal microbalance resonators,surface acoustic wave resonators, bulk acoustic wave resonators, andothers. Unlike these and other mechanical resonators, the electricalresonators may be not predictably affected by the changes change ofviscosity and/or density of the fluid. Instead, they may be predictablyaffected by the changes in the complex permittivity of the fluid.Electrical resonators may be very complicated in their design, forexample marginal oscillators require complicated multi-componentcircuits.

The degradation of at least some oils and lubricants may generatemolecules and/or other moieties that may be relatively more polar thanthe oil and lubricant from which they were formed. The base oil orlubricant may include long chain hydrocarbon molecules that are weaklypolar. Thus, the presence of polar contaminants may increase of one ormore parts of the oil's complex permittivity.

The degradation of at least some oils and lubricants may generatemolecules and/or other moieties that may be relatively low molecularweight and may be in the form of volatiles or gases. For example, aninsulating oil of an oil-fitted transformer is employed to insulate andsuppress corona and arcing and to serve as a coolant. However, theinsulating oil gradually deteriorates under the impact of electrical,thermal and environmental stresses during the life of the transformer.Different types of gases are generated in the insulating oil dependingon the deterioration processes. Examples of these gases includehydrogen, carbon monoxide, carbon dioxide, methane, ethane, ethylene,and acetylene. For example, thermal decomposition of mineral oilproduces hydrogen and methane. Thermal decomposition of cellulose andother solid insulation materials produces carbon monoxide, carbondioxide, and water vapor. Such gases are detected and monitored in realtime using multivariable sensors as described in more detail below. Forthis application the sensor is coated with a sensing material that isresponsive to one or more gases of interest. When the sensor is inoperational contact with the oil, dissolved gases in oil also interactwith the sensor and produce a predictable multivariable sensor response.The operational contact may be achieved by direct immersion of thesensor into oil when the sensing material is wetted by oil or through agas permeable membrane that may allow dissolved gases in oil to diffusethrough the membrane to the sensing material while the oil is notwetting the sensing material.

According to one example, the resonant transducers operate asre-configurable resonant structures and operate at multiple frequenciesfor monitoring of a status of fluids (and, further, for example, thehealth of equipment in contact with such fluids) and to probe moreaccurately dielectric properties of any samples in the presence ofuncontrolled ambient environmental noise contributions. Monitoring thehealth of fluids involves a determination of composition or adetermination of contamination of such fluid.

Non-limiting examples of interferents and ambient environmental noisecontributions include temperature and presence of interferences in asample. The term “interference” includes any undesired environmentalparameter that adversely affects the accuracy and precision ofmeasurements of the sensor. The term “interferent” refers to a materialor environmental condition that potentially may produce an erroneousresponse by the sensor. Filters (physical, chemical, and/or electronic)may be employed, based on the application specific parameters, toreduce, eliminate, or account for the presence and/or concentration ofsuch interferents.

With reference to FIG. 17, a sensing system 1700 is shown that may beuseful for assessing a fluid in contact therewith. The system 1700 mayrepresent one embodiment of the system 100 shown in FIG. 1. For purposesof illustration, a representative fluid may be engine oil. The systemmay include a fluid reservoir 1712 for a fluid and a sensor 1714. Thesensor 1714 may represent one embodiment of the sensor 108 shown inFIG. 1. Alternatively, the sensor may be set in a flow path of thefluid. The sensor may be a resonant sensor that is disposed in, or on,the reservoir, or may be coupled to in-line connectors in fluidcommunication with the fluid reservoir that define a flow path. In oneembodiment, the sensor may provide continuous monitoring of the fluidwithin the reservoir or flow path.

Suitable fluids may include hydrocarbon fuels and lubricants. Suitablelubricants may include engine oil, gear oil, hydraulic fluid,lubricating oils, synthetic based lubricants, lubricating fluids,greases, silicones, and the like. Suitable fuels may include gasoline,diesel fuel, jet fuel or kerosene, bio-fuels, petrodiesel-biodiesel fuelblends, natural gas (liquid or compressed), and fuel oils. Still otherfluids may be insulating oils in transformers, solvents, or mixtures ofsolvents. Still other fluids may be included with correspondinglyappropriate sensor parameters, such as water, air, engine exhaust,biologic fluids, and organic and/or vegetable oils. The fluid may be aliquid, or may in a gaseous phase. Further contemplated are multiphasecompositions. The fluids may be disposed in and/or used in connectionwith the operation of another system, such as the machine 102 shown inFIG. 1.

Non-limiting examples of various fluid components include unintendedleaks from proximate systems (e.g., radiator fluid into engine oil, orwater condensation in diesel fuel or transformer oil) and/or fromfluid-transport devices (e.g., valves, flanges, pipes, tubes). Otherdetectable fluid components may include degradation products of thefluid caused due to elevated temperature of operation, or due to contactwith oxidants (air, others). System operation may introduce fluidcomponents such as dirt, salt, soot or carbon, wear metal particles,wear products, and others. In some environments, fouling due to bacteriaor the like may be the fluid component. And in all instances, indirectmeasurement may be useful, such as a pH rise that indicates the presenceof an acidic component. Other detectable fluid components may includeexternal contaminants of the fluid.

The sensor may detect characteristics of the fluid via a resonantimpedance spectral response. One or more of the LCR resonators maymeasure the resonant impedance spectral response. As opposed to simpleimpedance measurements, the disclosed embodiments probe the sample withat least one resonant electrical circuit. The resonant impedancespectrum of the sensor in proximity to the sample (the sensor inoperational contact with the fluid) varies based on sample compositionand/or components and/or temperature. The measured resonant impedancevalues Z′ (which may be the real part of resonant impedance, Zre) and Z″(which may be the imaginary part of resonant impedance, Zim) reflect theresponse of the fluid (for example, the portion of the fluid inproximity to the sensor) to a stimulus of the electric field of theresonant electrical circuit.

The electrical field may be applied by the sensor via electrodes. Theelectrodes may be in direct or indirect electrical contact with thesample. For example, a sensor may be a combination of a sensing regionand associated circuits. The sensing region may be either bare or coatedwith a protective dielectric layer or a sensing layer. In each of thedisclosed cases, the sensing region may be considered to be inoperational contact with a fluid. In such embodiments, the tuningcircuits may not contact the fluid directly. One example of indirectelectrical contact with the sample may be when a sensing electrodestructure is coated with a dielectric protective coating and when theelectric field that may be generated between the electrodes interactswith the fluid after penetrating through the dielectric protectivecoating. A suitable dielectric protective coating may be conformallyapplied to the electrode.

Suitable sensors may include single use or multi-use sensors. A suitablemulti-use resonant sensor may be a re-usable sensor that may be usedduring the lifetime of a system in which it may be incorporated into. Inone embodiment, the resonant sensor may be a single use sensor that maybe used during all or part of a reaction or process. For example, theresonant sensor may include one or more pairs of electrodes and one ormore tuning elements, e.g., a resistor, a capacitor, an inductor, aresonator, impedance transformer, or combinations of two or more thereofto form an inductor-capacitor-resistor (LCR) resonant circuit operatedat one or more resonant frequencies. In certain embodiments, differentresonant circuits of a plurality of resonant circuits of a resonantsensor may be configured to resonate at different frequencies. Differentfrequencies may be selected to be across the dispersion profile of themeasured fluid composition. The dispersion profile may be a dependenceof the dielectric properties of the fluid composition on the probingfrequency. Various components of the fluid have different dispersionprofiles. When measured at multiple resonance frequencies,concentrations of different components of the fluid may be determined.

Data from the resonant sensor may be acquired via data acquisitioncircuitry 1716, which may be associated with the sensor or which may beassociated with a control system, such as a controller or workstation1722 including data processing circuitry, where additional processingand analysis may be performed. The controller or workstation may includeone or more wireless or wired components, and may also communicate withthe other components of the system. Suitable communication modelsinclude wireless or wired. At least one suitable wireless model includesradio frequency devices, such as RFID wireless communications. Otherwireless communication modalities may be used based on applicationspecific parameters. For example, where there may be EMF interferencecertain modalities may work where others may not. The data acquisitioncircuitry can be disposed within the fluid reservoir as shown in FIG.18. Other suitable locations may include disposition being within theworkstation. Further, the workstation can be replaced with a controlsystem of the whole process where the resonant sensor and its dataacquisition circuitry may be connected to the control system of process.

During operation, the monitoring process may couple to, among otherthings, operation of an internal combustion engine, an oil-filledtransformer, a chemical reaction process, a biological reaction process,purification and/or separation process, a catalytic process, a generalcombustion process, production of raw oil, production of raw gas,material extraction, material transport, and other industrial processes.The data acquisition circuitry may be in the form of a sensor reader,which may be configured to communicate wirelessly or wired with thefluid reservoir and/or the workstation. For example, the sensor readermay be a battery-operated device and/or may be powered using energyavailable from the main control system or by using harvesting of energyfrom ambient sources (light, vibration, heat, or electromagneticenergy).

Additionally, the data acquisition circuitry may receive data from oneor more resonant sensors 1714 (e.g., multiple sensors formed in an arrayor multiple sensors positioned at different locations in or around thefluid reservoir). The data may be stored in short or long term memorystorage devices, such as archiving communication systems, which may belocated within or remote from the system and/or reconstructed anddisplayed for an operator, such as at the operator workstation.Non-limiting examples of positioning and installations of sensors andsensor systems of the present techniques include fuel or fluidreservoirs, associated piping components, connectors, flow-throughcomponents, and any other relevant process components.

In addition to displaying the data, the operator workstation may controlthe above-described operations and functions of the system. The operatorworkstation may include one or more processor-based components, such asgeneral purpose or application specific computers 1724. In addition tothe processor-based components, the computer may include various memoryand/or storage components including magnetic and optical mass storagedevices, internal memory, such as RAM chips. The memory and/or storagecomponents may be used for storing programs and routines for performingthe techniques described herein that may be executed by the operatorworkstation or by associated components of the system. Alternatively,the programs and routines may be stored on a computer accessible storageand/or memory remote from the operator workstation but accessible bynetwork and/or communication interfaces present on the computer. Thecomputer may also comprise various input/output (I/O) interfaces, aswell as various network or communication interfaces. The various I/Ointerfaces may allow communication with user interface devices, such asa display 1726, keyboard 1728, electronic mouse 1730, and printer 1732,that may be used for viewing and inputting configuration informationand/or for operating the imaging system. Other devices, not shown, maybe useful for interfacing, such as touchpads, heads up displays,microphones, and the like. The various network and communicationinterfaces may allow connection to both local and wide area intranetsand storage networks as well as the Internet. The various I/O andcommunication interfaces may utilize wires, lines, or suitable wirelessinterfaces, as appropriate or desired.

The sensor may include a plurality of resonant circuits that may beconfigured to probe the fluid in the fluid reservoir with a plurality offrequencies. The fluid reservoir may be a reservoir bound by theengineered fluid-impermeable walls or by naturally formedfluid-impermeable walls or by the distance of the electromagnetic energyemitted from the sensor region to probe the fluid. Further, thedifferent frequencies may be used to probe a fluid sample at differentdepths. In certain embodiments, an integrated circuit memory chip may begalvanically coupled to the resonant sensor. The integrated circuitmemory chip may contain different types of information. Non-limitingexamples of such information in the memory of the integrated circuitchip include calibration coefficients for the sensor, sensor lot number,production date, end-user information. In another embodiment, theresonant sensor may comprise an interdigital structure that has afluid-sensing region.

In certain embodiments, when an integrated circuit memory chip may begalvanically coupled to the resonant sensor, readings of the sensorresponse may be performed with a sensor reader that contains circuitryoperable to read the analog portion of the sensor. The analog portion ofthe sensor may include resonant impedance. The digital portion of thesensor may include information from the integrated circuit memory chip.

FIG. 18 illustrates a non-limiting example of a design of the resonantsensor. A sensing electrode structure 1834 of the sensor may beconnected to the tuning circuits and the data acquisition circuitry. Thesensing electrode structure 1834 can be bare and in direct contact withthe fluid. Alternatively, the sensing electrode structure can be coatedwith a protective or sensing coating 1836. The sensing electrodestructure, without or with the protective or sensing coating, forms asensing region 1838. The coating may be applied conformably, and may bea dielectric material. The sensing electrode structure, without or withthe protective coating that forms the sensing region, may operationallycontact a fluid. The fluid contains the analyte or contaminant(s). Thesensing electrode structure may be either without (bare) or with aprotective coating. A bare sensing electrode structure may generate anelectric field between the electrodes that interacts directly with thefluid. A dielectric protective coated sensing electrode structure maygenerate an electric field that is between the electrodes that interactswith the fluid after penetrating through the dielectric protectivecoating. In one embodiment, the coating may be applied onto electrodesto form a conformal protective layer having the same thickness over allelectrode surfaces and between electrodes on the substrate. Where acoating has been applied onto electrodes to form a protective layer, itmay have a generally constant or variable final thickness over thesubstrate and sensor electrodes on the substrate. In another embodiment,a substrate simultaneously serves as a protective layer when theelectrodes are separated from the fluid by the substrate. In thisscenario, a substrate has electrodes on one side that do not directlycontact the fluid, and the other side of the substrate does not haveelectrodes that face the fluid. Detection of the fluid may be performedwhen the electric field from the electrodes penetrates the substrate andinto the fluid. Suitable examples of such substrate materials mayinclude ceramic, aluminum oxide, zirconium oxide, and others.

FIG. 19 illustrates a portion of a resonant sensor system 1900 having asingle sensing region 1938, and employed in a sensor assembly 1940useful to probe a fluid sample using a plurality of frequencies. Thesensing region may be disposed on a substrate and may include a suitablesensing material. In some embodiments, the substrate of the sensor maybe a dielectric substrate. In some embodiments, the sensor assembly mayinclude a plurality of tuning elements 1942. The plurality of tuningelements may be operatively coupled to the single sensing region todefine a plurality of resonant circuits. The tuning elements along withthe single sensing region may define a plurality of resonant circuits.Each resonant circuit of the plurality of resonant circuits may includeone or more tuning elements of the plurality of tuning elements. Notshown is a semi-permeable film, semi-permeable membrane, orsemi-permeable inorganic barrier (collectively a “selective barrier”)that allows (or prevents) selective analytes or contaminants through theselective barrier and into the sensing region.

Suitable interdigital electrode structures for probing a fluid sampleinclude two- and four-electrode structures. Suitable materials forelectrodes include stainless steel, platinum, gold, noble metals, andothers. Suitable materials of a substrate and/or a dielectric protectivelayer may include silicon dioxide, silicon nitride, parylene, silicone,fluorinated polymers, alumina, ceramics, and others. Suitable examplesof sensing layers include semiconducting materials, metal oxides,nanocomposites, polymers, or the like. Suitable electrodes may be formedusing metal etching, screen-printing, ink-jet-printing, and mask-basedmetal deposition techniques. The thickness of fabricated electrodes onthe substrates may be in a range of from about 10 nanometers to about1000 micrometers. The materials for the interdigital electrodestructures, substrate, dielectric protective layer, sensing layer, andelectrode formation methods may be selected based at least in part onthe application specific parameters.

As shown in the illustrated embodiment, the plurality of tuning elementsmay be disposed external to the sensor. However, in one embodiment, thetuning elements may be disposed on the substrate of the sensor. Inanother embodiment, some of the plurality of tuning elements may beexternal to the sensor substrate, while other tuning elements may bedisposed on the substrate. The tuning elements may comprise a resistor,a capacitor, an inductor, a resonator, impedance transformer, orcombinations thereof.

The sensor assembly 1940 may include a controller that has a multiplexer1944. The multiplexer may facilitate electronic switching between thetuning elements. The multiplexer may select one or more signalsassociated with the probing frequencies and forward the selected signalto an output device or a reader, such as the reader 106. In oneembodiment, the multiplexer may selectively send signals to an outputdevice or a reader. The multiplexer may send a plurality of signalssimultaneously to a sensor reader. The multiplexer may facilitateelectronic switching between the sensing regions.

During operation, each resonant circuit may resonate at a definedfrequency. At least one resonant circuit may resonate at a frequencythat may be different from the resonating frequency of the otherresonant circuits. By way of example, if the sensing region includes apair of electrodes, the tuning elements may be a resistor, a capacitor,and an inductor to form an inductor-capacitor-resistor (LCR) resonantcircuit. The tuning elements may be electrically coupled to the sensingregion. In one embodiment, the tuning elements may be in parallelconnection to the sensing region. In certain embodiments, the differentresonant circuits of the plurality of resonant circuits may beconfigured to resonate at different frequencies. The different resonantcircuits may be configured to probe the fluid sample with a plurality ofresonant frequencies. The different resonant frequencies may be used toprobe a fluid sample over the frequency range of spectral dispersions offluid components. The spectral dispersions of fluid components mayinclude spectral dispersions of external contaminants of the fluid andaging of the fluid. The spectral dispersions that may be monitored withthe sensors of the present disclosure may be over a frequency range offrom about 0.1 Hz to about 100 GHz and include alpha, beta, gamma,delta, and other types of spectral dispersions as constrained byapplication specific parameters.

FIG. 20 illustrates another sensor circuit 2010. The sensing region 1938(shown with variable resistor and capacitor) is combined with tuningcomponents 1942 (shown with variable inductance and capacitance). Torealize sensor response at different frequency range, additional circuitelements may be utilized to tune the frequency range. Therefore, asensor can be operating at multiple frequency ranges by using a definedor selected combination of extra circuit components—such as inductors,capacitors, and impedance transformers. These components may beconnected in parallel or in series, as needed, to the sensor to vary theoperating frequency range. The controller may control the impedancetransformer ratio to affect the sensitivity. A sensor's frequencyresponse and its magnitude may be based at least in part on the overallinput resonant impedance changes due to the sensor's response to thecell's status, its behavior, and the like. Thus, the sensor'ssensitivity may be controlled through the dynamic tunability of thetransformer ratio. Tuning the response of each channel may be achieved,for example, by using one or more inductors. In one embodiment, wirelessreadout from the electrodes may provide an improvement in responseselectivity and sensitivity. In one embodiment, transformer basedcoupling may reject parasitic LCR components from instrumentation(analyzer, cables, amongst others). The LCR resonator in FIG. 20 has arelatively simple design as compared to other resonators, for example ascompared to marginal oscillators that require complicatedmulti-component circuits for their operation that include a currentfeedback amplifier and other components.

As noted herein, a suitable wireless sensor may be radio-frequencyidentification (RFID) sensor where a passive RFID tag may be adapted toperform a sensing function. With reference to FIGS. 21 and 22, anembodiment is shown in which the resonant sensor may be an adapted RFIDtag. In FIG. 21 a resonant antenna 2150 and memory chip 2152 may becoated with a protective material or sensing material 2156. The sensingmaterial may be a sensing region of the RFID tag. In FIG. 22, thesensing region 1938 (that can optionally include the protective orsensing material) may be attached across an antenna. In both cases(FIGS. 21 and 22), the electrical response of the sensing region may betranslated into changes in the resonant impedance response of thesensor. An RFID sensor having a memory chip may operate with a frequencydetermined at least in part by the operating frequency used the memorychip. That is, some operating frequencies (of the sensor and the chip)may interfere with each other and may be less desirable to havedisruptive harmonics or destructive waveforms. And, the sensor can havea circular, square, cylindrical, rectangular, or otherappropriately-shaped sensing region and/or antenna.

The resonant frequency of an antenna circuit may be set to a higherfrequency than a resonant frequency of the sensor circuit. The frequencydifferential may be in a range of from, for example, as much as about 4times to about 1000 times higher. In one embodiment, the sensor circuitmay have a resonant frequency that may respond to a determined sensedenvironmental condition. The two resonant circuits may be connected sothat when alternating current (AC) energy is received by the antennaresonant circuit, it may apply direct current energy to the sensorresonant circuit. The AC energy may be supplied through the use of adiode and a capacitor, and the AC energy may be transmitted to thesensor resonant circuit through an LC tank circuit through either a tapwithin the L of the LC tank circuit or a tap within the C of the LC tankcircuit. Further, the two resonant circuits may be coupled such thatvoltage from the sensor resonant circuit may change the impedance of theantenna resonant circuit. The modulation of the impedance of the antennacircuit may be accomplished through the use of a transistor, for examplea FET (field-effect transistor).

The RFID sensor's memory chip may be optional. The RFID sensor without amemory chip can be a resonant LCR sensor and can operate at differentfrequency ranges from a kilohertz to several gigahertz. That is, thememory chip's absence may widen the available frequency range.

Suitable sensing materials and sensing films as disclosed herein mayinclude materials deposited onto the sensor to perform a function ofpredictably and reproducibly affecting the resonant impedance sensorresponse upon interaction with the environment. For example, aconducting polymer, such as polyaniline, changes its conductivity uponexposure to solutions of different pH. That is, the resonant impedancesensor response changes as a function of pH when such a conductingpolymer film is deposited onto the RFID sensor surface. Thus, such anRFID sensor works as a pH sensor.

As one example of gaseous fluid detection, when such a polyaniline filmis deposited onto the RFID sensor for detection in gas phase, thecomplex resonant impedance sensor response also changes upon exposure tobasic (for example, NH₃) or acidic (for example, HCl) gases. Suitablesensor films include polymer, organic, inorganic, biological, composite,and nano-composite films that change their electrical and or dielectricproperty based on the environment in which they may be placed. Otherexamples of sensor films may be a sulfonated polymer such ascommercially available Nafion, an adhesive polymer such as siliconeadhesive, an inorganic film such as sol-gel film, a composite film suchas carbon black-polyisobutylene film, a nano-composite film such ascarbon nanotube-Nafion film, gold nanoparticle-polymer film, metalnanoparticle-polymer film, zeolites, metal-organic frameworks, cagecompounds, clathrates, inclusion compounds, semiconducting materials,metal oxides, electrospun polymer nanofibers, electrospun inorganicnanofibers, electrospun composite nanofibers, and other sensor materialsselected based on application specific parameters. To reduce or preventthe material in the sensor film from leaking into the liquidenvironment, the sensor materials may be attached to the sensor surfaceusing standard techniques, such as covalent bonding, electrostaticbonding and other techniques. Some sensing materials may require acertain temperature for efficient operation. A non-limiting range ofoperating temperatures of the sensing materials and associated sensorsonto which the sensing materials are deposited is between −260 degreesCelsius and 1600 degrees Celsius.

In one embodiment, the system may measure a resonant impedance {hacekover (Z)}(f) (represented by Eq. (1)) of the sensor.

{hacek over (Z)}(f)=Z _(re)(f)+jZ _(im)(f)  Eq. (1)

where Z_(re)(f) may be the real part of the resonant impedance andZ_(im)(f) may be an imaginary part of the resonant impedance. In oneembodiment, the resonant impedance spectral response of the sensor maybe a multivariable response as more than one frequency may be utilizedto measure sensor response across the resonance of the sensor. In someembodiments, the resonant impedance response of the sensor may be amultivariable response because more than one frequency may be utilizedto measure sensor response outside the resonance peak of the sensor. Insome embodiments, the sensor response may be measured at multiplefrequencies across the resonance of the sensor. For example, if thesensor resonates at about 1 MHz, the measured frequencies and associatedsensor responses may be measured from about 0.25 MHz to about 2 MHz.This multivariable response may be analyzed by multivariate analysis.The multivariable response of the sensor includes the sensor's fullresonant impedance spectral response and/or several individuallymeasured properties, such as but not limited to F_(p), Z_(p), F_(z), F₁,F₂, Z₁, and Z₂. As used herein, the term “resonant impedance spectralresponse” may be referred to as “resonant impedance spectra”.

FIG. 23 depicts a graph of measured resonant impedance parameters of anembodiment of the resonant sensor, in accordance with embodiments of thepresent technique. These and other measured properties may be “spectralparameters.” The measured properties may be also called “signals” or“output signals”. These properties include the frequency of the maximumof the real part of the resonant impedance (F_(p), resonance peakposition), magnitude of the real part of the resonant impedance (Z_(p),peak height), zero-reactance frequency (F_(z), frequency at which theimaginary portion of resonant impedance may be zero), resonant frequencyof the imaginary part of the resonant impedance (F₁), and anti-resonantfrequency of the imaginary part of the resonant impedance (F₂), signalmagnitude (Z₁) at the resonant frequency of the imaginary part of theresonant impedance (F₁), and signal magnitude (Z₂) at the anti-resonantfrequency of the imaginary part of the resonant impedance (F₂). Otherparameters may be measured using the entire resonant impedance spectra,for example, quality factor of resonance, phase angle, and magnitude ofresonant impedance. The measured “output signals” may be from a resonantsensor or from a non-resonant sensor.

For measurements of fluid properties in fluid reservoirs, sensors withtheir sensing regions can be designed to fit standard ports or speciallymade ports in the reservoirs. Suitable design examples are depicted inFIG. 24 and FIG. 25. One example is provided of a resonant sensor 2450with an aligned sensing region 2451. The sensing region defines a firstAxis A, which is perpendicular to a transverse axis labeled Axis B. Aninsertion port structure 2453 defines an insertion aperture 2454 that iselongated along Axis A. The sensing region, then, is arranged parallelto the port's elongated aperture, translation along Axis B allows forsensor region insertion into the port and to contact a measured fluid.One example of another resonant sensor 2555 in which the sensing region2556 is not constrained by its shape relative to an aperture 2557defined by a port structure 2558 is depicted in FIG. 25. Alignment pins,not shown, may be used to align the sensor, and the sensing region,relative to the port aperture, as may be desired.

Measurements of fluid properties in fluid reservoirs may be performedusing sensors with their sensing regions exposed to the fluid as shownin FIGS. 26 and 27. The sensor 2655 shown in FIG. 26 is installed in afluid transfer pipe 2659A, and is coupled to a sensor reader 2659B. Thesensor reader 2659B may be coupled by wire or cable, and locatedproximate to the sensor 2655 as shown in FIG. 26. In another embodiment,the sensor reader 2659B may be directly connected to the sensor withouta cable—as shown in FIG. 27. During operation, a fluid flows through thepipe and contacts the sensing region 2556. As the sensing region 2556senses an analyte of interest it signals the sensor reader 2659B.

The sensor reader (also referred to as micro-analyzer) has beendeveloped with a small form factor, low power consumption and low costof components. FIGS. 28A-C are graphs depicting measurements related tothe sensor reader according to one embodiment. FIG. 28A is a comparisonof power consumption, size, and weight between a desktop analyzer andthe developed micro-analyzer. FIG. 28A depicts that the design of themicro-analyzer provided 100-500-fold reduction in power consumption,size, and weight as compared to desktop analyzers. These advancementsmake the sensor reader attractive for a wide range of applicationsincluding monitoring of industrial fluids, where laboratory analyzersare size-, power-, and cost-prohibitive. FIGS. 28B and 28C depictmeasured Fp and Zp noise levels of the developed micro-analyzer,respectively. The developed sensor reader has a 1 □ □Fp noise of ˜5 Hzand 1 □Zp noise of 0.006 ohm. This electronic design of the sensorreader provided 4-14 times reduction in noise levels in measurements of{hacek over (Z)}(f) spectra as compared to measurements with alaboratory desktop analyzer with Fp noise=60 Hz and Zp noise=0.025 Ohm.

A flow diagram of a method 2860 is shown in FIG. 29. In one embodiment,a method for monitoring of oil health includes immersion of the sensorinto an fluid, such as oil (step 2862) and measurement of electricalresonance parameters of the resonance spectra (step 2864) at severalresonances of a single sensor. For quantitation of contamination ofengine oil by water, fuel leaks, and soot with a sensor, the sensor maybe placed into operational contact with the fluid at step 2862. In aspecific embodiment, the resonant impedance spectra {hacek over(Z)}(f)=Z_(re)(f)+jZ_(im)(f) of a sensor may be determined at step 2864.For example, the parameters from the measured {hacek over (Z)}(f)spectra such as the frequency position F_(p) and magnitude Z_(p) ofZ_(re)(f) and the resonant F₁ and antiresonant F₂ frequencies, theirmagnitudes Z₁ and Z₂ of Z_(im)(f), and zero-reactance frequency Fz ofZ_(im)(f), may be calculated. In another embodiment, the electricalresonance parameters may include capacitance parameters of the sensor inoperational contact with the fluid, instead or in addition to impedanceparameters.

The method 2860 classifies the electrical resonance parameters at step2870. This may be done using a determined classification model 2872 toassess, for example, one or more of water effects 2874, fuel effects2875, and temperature effects 2876. Quantitation of the electricalresonance parameters may be performed at step 2880 by using apredetermined, earlier saved quantitation model 2882, and determinationof components 2886 in oil such as water, fuel, soot, and wear metalparticles 2890 as well as the temperature 2892, and prediction of theoil health 2898 and the engine health 2901. This may be done by usingone or more of determined engine health descriptors 2902 and oil healthdescriptors 2904 as well as inputs from any additional sensors 2908.Suitable additional sensors may include those sensing corrosion,temperature, pressure, system (engine) load, system location (e.g., byGPS signal), equipment age calculator, pH, and the like.

For example, in one embodiment, a sensor system may be an electricalresonator that may be excited with a wired or wireless excitation andwhere a resonance spectrum may be collected and analyzed to extract atleast four parameter that may be further processed upon auto scaling ormean centering of the parameters and to quantitatively predict theconcentrations of water and fuel in engine oil and to predict theremaining life of the engine oil and/or the remaining life of theengine. The spectral response of the resonance spectrum such as F_(p),Z_(p), F_(z), F₁, F₂, Z₁, and Z₂ or the whole resonance spectrum with asingle or multiple resonators can be used for data processing.

The classification model (see model 2872 in FIG. 29) may be built usingthe predicted contributions of the spectral parameters for anuncontaminated fluid and for fluid contamination using previouslydetermined component effects and their corresponding spectralparameters. Such effects may be quantified (e.g., see quantitation model2882 in FIG. 29) to predict if a measured or sensed fluid has any watereffects, fuel leak effects, or temperature effects. That is, based onpreviously or empirically determined effects of components on aparticular fluid, the resonance parameters, both real and imaginary, maybe affected in a quantifiable manner if components of interest arepresent. Further, based on the measured parameters, a concentration of aparticular component may also be predicted, and multi-component modelsmay be generated. The disclosed techniques may be used to sense asuitable fluid and to build a component and environmental effect model.

In one embodiment, measurements of properties of fluids may be performedat two or more temperatures of the fluid. Measurements at differenttemperatures provide information about species of interest and otherspecies (chemical constituents) in the fluid when measured as thefrequency dispersion profiles over the broad frequency range or whenmeasured as frequency responses over the relatively narrow frequencyrange. Performing analysis of resonant impedance spectra of the sensorcollected at different temperatures and determining two or moreproperties of the fluid per temperature based on the analyzed resonantimpedance spectra allows an improvement of the sensor accuracy ofdeterminations of properties of species of interest. This improvementmay be due to differences of frequency responses of species of interestand other species in the fluid as a function of temperature caused bythe molecular structure of these different species. Measurements atdifferent temperatures may be performed with a resonant sensor that hasa thermal element in thermal contact with the sensing region of theresonant sensor. The thermal element produces a local change intemperature of the fluid which may be in proximity to the sensingregion. This local temperature change can be above or below thetemperature of the bulk of the fluid in the container with the sensor.Non-limiting examples of thermal elements include a Peltier cooler,thin-film heater, and pencil heater. The thermal element can produce alocal change in temperature of the fluid in the range from about 1degree Celsius to about 50 degrees Celsius.

In one embodiment, measurements of properties of fluids may be performedto determine dynamic signatures of the changes of chemical constituentsin the fluid. The time scales of these dynamic signatures may varygreatly. Suitable timescale in a range of from about 1 second to about200 days may be useful to determine different types of leaks of fluidsin engines. Such determinations allow the identification of dynamicsignatures of the leaks in an engine, relation of the identifiedsignature with the known leak signature from a specific enginecomponent, and determination of the location of the leak based on thesignature.

Measurements of properties of fluids may be performed at extremetemperature conditions. Depending on the application, these conditionsmay range from temperatures down to about −260 degrees Celsius and totemperatures up to about +1600 degrees Celsius. Such harsh temperatureconditions with negative temperature down to about −260 degrees Celsiusmay be useful in relation to liquefied natural gas (LNG) and in thestorage of biological and other types of samples. Harsh temperatureconditions with positive temperature of up to about +1600 degreesCelsius may be useful in monitoring equipment where the temperature ofoperating components of the equipment can reach about +1600 degreesCelsius. Examples of equipment that operates at about 250 degreesCelsius may include downhole equipment in oil and gas production and theoperations of an internal combustion engine (diesel, natural gas,hydrogen (direct combustion or fuel cells), gasoline, combinationsthereof, and the like) for one or more of the fuel, the lubricationsystem, and the cooling/radiator system. Another example of suchequipment may include an oil-filled transformer. Examples of equipmentthat operates at about 1000 and up to 1500 degrees Celsius include gasturbines. Examples of equipment that operates at about 1600 degreesCelsius include aircraft jet engines.

The applicability of multivariable electrical resonators may bedemonstrated by detection of engine oil contamination from water anddiesel fuel and determinations of water in model fluid such as dioxanethat has the dielectric constant similar to oil. Determination ofresolution of the sensor measurements may be performed using hexane andtoluene as model systems. Samples of some engine oil were obtained fromGE Transportation, while other chemicals may be commercially obtainedfrom Aldrich.

Measurements of the resonant impedance of sensors may be performed witha network analyzer (Agilent) or a precision impedance analyzer(Agilent), under computer control using LabVIEW. Collected resonantimpedance data may be analyzed using KaleidaGraph (Synergy Software,Reading, Pa.) and PLS Toolbox (Eigenvector Research, Inc., Manson,Wash.) operated with Matlab (The Mathworks Inc., Natick, Mass.).

Different amounts of fuel and water leaks into oil may be determinedquantitatively and experimentally with a single multivariable resonantsensor. Suitable oil may be railroad internal combustion engine oil.Suitable fuel may be diesel fuel. Binary and ternary mixtures of waterand fuel in oil may be produced in different proportions. Concentrationsof water may be 0, 0.1% and 0.2% (by volume). Concentrations of fuel maybe 0, 3% and 6% (by volume).

The resonance spectra from measured samples may be processed and theprocessed data served as inputs to the principal components analysis(PCA) tool. PCA may be a pattern recognition method that explains thevariance of the data as the weighted sums of the original variables,known as principal components (PCs). A highlight of detection of waterin mixtures of engine oil, water, and fuel may be illustrated in FIG. 30that depicts a scores plot of a developed PCA model. A highlight ofdetection of fuel in mixtures of engine oil, water, and fuel may beillustrated in FIG. 31 that depicts a scores plot of a developed PCAmodel. In FIGS. 30 and 31, concentrations of water of 0.1% and 0.2% arelabeled as W0.1 and W0.2, respectively. Concentrations of fuel of 3% and6% are labeled as D3 and D6, respectively. The multivariable response ofthe resonant transducers originates from the measured whole resonancespectra of the transducer followed by the processing of these spectrausing multivariate analysis tools. For quantitation of contamination ofengine oil by water and fuel leaks with a single multivariable sensor,the resonant impedance spectra {hacek over (Z)}(f)=Z_(re)(f)+jZ_(im)(f)of the resonant transducer may be measured. Several parameters from themeasured {hacek over (Z)}(f) spectra may be calculated that included thefrequency position F_(p) and magnitude Z_(p) of Z_(re)(f) and theresonant Fi and antiresonant F₂ frequencies, their magnitudes Z₁ and Z₂of Z_(im)(f), and zero-reactance frequency F_(z) of Z_(im)(f) as shownin FIG. 23.

By using multivariate analysis of calculated parameters of {hacek over(Z)}(f) spectra, classification of analyte may be performed. Suitableanalysis techniques for multivariate analysis of spectral data from themultivariable sensors may include Principal Components Analysis (PCA),Independent Component Analysis (ICA), Linear Discriminant Analysis(LDA), and Flexible Discriminant Analysis (FDA). PCA may be used todiscriminate between different vapors using the peptide-based sensingmaterial. A loadings plot of the PCA model is illustrated in FIG. 32.This plot illustrates the contributions of individual components fromthe resonance spectrum. The plot shows that all components such as Fp,F1, F2, Fz, Zp, Z1, and Z2 had contributions to the sensor response.

Quantitation of water and fuel in oil in their binary and ternarymixtures may be further performed with a single multivariable resonantsensor using PLS Toolbox (Eigenvector Research, Inc., Manson, Wash.)operated with Matlab (The Mathworks Inc., Natick, Mass.). FIG. 33 showsa correlation plot between actual (measured) and predictedconcentrations of water in water/fuel/oil mixtures using a singleresonant sensor. FIG. 34 shows a correlation plot between measured andpredicted concentrations of fuel in water/fuel/oil mixtures using asingle resonant sensor. Prediction errors of simultaneous quantitationof water and fuel in oil with the single sensor may be 0.02% of waterand 1.3% of fuel.

In another example, sensor resolution may be determined in multi-partexperiments. In a first experiment, hexane and toluene may be used asmodel chemicals to determine the ability of the sensor to resolvedifferences in the dielectric constant. Hexane has the dielectricconstant of 1.88 while toluene has the dielectric constant of 2.38. Adeveloped sensor may resolve these two liquids with the resolution ofthe dielectric constant of 0.0004-0.0012. Expected results are shown inFIG. 35. In the second experiment, 1,4-dioxane may be used as a modelchemical for oil because of its the dielectric constant similar to oiland the ability to be easily miscible with water. The sensor may resolvewater additions into dioxane down to 7-20 ppm. Expected results areshown in FIG. 36 illustrating that the developed sensor may be able toresolve water additions into dioxane (model system for oil) down to 7-20ppm with water additions done in increments of 200 ppm.

In another example, water and soot (carbon black) additions may be doneto dioxane and measured with a sensor. Water additions may be done as500 ppm, 1000 ppm, and 2500 ppm additions. Soot (carbon black) may beadded as 100 ppm carbon black with 2500 ppm of water. Exemplaryresonance spectra of a sensor are presented in FIGS. 37 and 38. Resultsof multivariate analysis are presented in FIG. 39. FIG. 37 shows thereal part Z_(re(f)) and FIG. 38 shows imaginary part Z_(im(f)) ofresonant impedance. Measured samples may be: (0) clean model oil(dioxane); (1) addition of 500 ppm of water; (2) addition of 1000 ppm ofwater, (3) addition of 2500 ppm of water; (4) addition of 2500 ppm ofwater and 100 ppm of soot (carbon black). FIG. 39 shows a scores plot ofPrincipal component 1 (PC1) vs. Principal component 2 (PC2) illustratingspectral relation between sensor responses to different types ofcontamination. Samples may be: (0) clean model oil (dioxane); (1)addition of 500 ppm of water; (2) addition of 1000 ppm of water; (3)addition of 2500 ppm of water; (4) addition of 2500 ppm of water and 100ppm of soot (as carbon black).

In another example, a multiresonant sensor system may be built with fourresonant frequencies. The 1,4-dioxane can be used as a model chemicalfor oil, because its dielectric constant is somewhat similar to oil andit is miscible with water. Water additions may be done to dioxane andmeasured with a sensor. Four example resonance spectra of the sensor arepresented in FIGS. 39 and 40. These values illustrate that thedispersion profile of the sensor in non-contaminated dioxane (as shownin FIG. 40) has changed its shape upon addition of water (as shown inFIG. 41). Also, the widths and the magnitudes of the resonance peakshave been modified by water addition.

In another example, sensor electrode geometries and resonant frequencymay be optimized for the maximum Fp and Zp responses to water. Atwo-factor design of experiments may be done by varying interdigitalelectrode (IDE) spacing D and electrode width W, where D=W=150, 300, 450micrometers (μm) and varying resonance frequency, Fp, as Fp=20, 35, 50MHz (in air). Measurements may be performed by adding water to dioxaneat 5000 ppm concentration. FIG. 42 shows effects of sensor design onsensitivity of Fp measurements. FIG. 43 shows effects of sensor designon sensitivity of Zp measurements. A 300 μm IDE spacing and 50 MHzoperation frequency yielded both strong Fp and Zp signals.

In another example shown in FIG. 44, determination of water in oil maybe performed by circulating oil in a test loop and adding water at 2000ppm increments to generate water concentrations in oil of 2000 ppm, 4000ppm, and 6000 ppm. Measurements may be performed using two resonantsensors. Sensor 1 had area of 2 cm² with the electrode width/spacing of0.4 mm/0.4 mm and resonating at 80 MHz in air. Sensor 2 may be one ofgeometries from the design of experiments and had area of 4 cm² with theelectrode width/spacing of 0.15 mm/0.15 mm and resonating at ˜50 MHz inair. The limit of detection of water in oil may be determined at thesignal-to-noise level of three to be 3-12 ppm (Sensor 1) and 0.6-2.6 ppm(Sensor 2) based on the measured sensor noise levels and signal levelsat 2000 ppm of added water.

In another example, determination of water in oil at different oiltemperatures may be performed by circulating oil in a test loop andadding water at 400 ppm increments to generate water concentrations inoil of 400 ppm, 800 ppm, 1200 ppm, and 1600 ppm. The nominaltemperatures of oil may be T1=80 degrees Celsius, T2=100 degreesCelsius, and T3=120 degrees Celsius as produced by a thermal bath. FIG.45 depicts a scores plot of a developed PCA model illustrating thatresponses of the resonant sensor to additions of water at differenttemperatures may be in different directions. Each individual arrow inFIG. 45 points in the direction of increasing water concentrations atoil temperatures T1, T2, and T3. FIG. 46 may depict results ofmultivariate linear regression model using partial least squares (PLS)technique to quantify water concentrations in oil using responses of thesingle sensor. The PLS technique may determine correlations between theindependent variables and the sensor response by finding the directionin the multidimensional space of the sensor response that explains themaximum variance for the independent variables. FIG. 47 shows that suchmultivariate linear regression may be able to predict waterconcentrations independent of oil temperature.

Analysis of this sensor data of determination of water in oil (0 ppm,400 ppm, 800 ppm, 1200 ppm, and 1600 ppm) at different nominaltemperatures of oil (80 degrees Celsius, 100 degrees Celsius, and 120degrees Celsius) may be performed using a multivariate non-linear(quadratic) regression. FIG. 47 depicts the actual (measured)concentrations of water in oil at three temperatures (solid line) andpredicted concentrations (open circles). FIG. 48 depicts predictionerror between actual and predicted concentrations of water in oil atthree temperatures. FIG. 49 depicts a correlation plot between actual(measured) and predicted concentrations of water in oil at threetemperatures.

Analysis of this sensor data of determination of water in oil (0 ppm,400 ppm, 800 ppm, 1200 ppm, and 1600 ppm) at different nominaltemperatures of oil (80 degrees Celsius, 100 degrees Celsius, and 120degrees Celsius) may be further performed using a multivariatenon-linear (quadratic) regression with an additional input from atemperature sensor positioned in measured oil. FIG. 50 depicts theactual (measured) concentrations of water in oil at three temperatures(solid line) and predicted concentrations (open circles). FIG. 51depicts prediction error between actual and predicted concentrations ofwater in oil at three temperatures. FIG. 52 depicts a correlation plotbetween actual (measured) and predicted concentrations of water in oilat three temperatures.

The performance of this developed resonant sensor may compare with theperformance of a standard non-resonant capacitance sensor that served asa reference capacitance sensor. This reference capacitance sensor hastwo co-axis pipes, and it is possible to measure capacitance of thefluid being tested by applying a sinusoidal signal to the inner pipe.The comparison may be performed by having both sensors in the samecirculating-oil loop where water leaks may be introduced and presentedto both sensors. Water leaks levels may be 25, 25, 50, 100, 200, 500,and 1000 ppm. FIG. 53 depicts the response of a reference capacitancesensor to water leaks into engine oil at levels of 25, 25, 50, 100, 200,500, and 1000 ppm each. This figure illustrates that the referencecapacitance sensor did not show an appreciable signal change from itsnoise until water leaks of 25, 25, 50, 100, and 200 ppm 200 ppm may beintroduced. In contrast, FIG. 54 shows the response of a resonant sensoraccording to an embodiment to water leaks into engine oil where thissensor may detect the smallest water leak at 25 ppm and detected allother water leaks presented to both sensors.

The resonant sensor may be tested in a single cylinder locomotive enginetest bed for about 34 days. FIG. 55 is a graph depicting results oftemperature of oil and sensor response after operating the developedresonant sensor in a single cylinder locomotive engine test bed for aperiod of 34 days. FIG. 56 illustrates a correlation between response ofthe developed resonant sensor in a single cylinder locomotive engine forabout 34 days and the temperature of oil.

In another example, sources of leaks in an engine may be determined byidentifying dynamic signatures of the leaks, relating the identifiedsignature with a known leak signature from a specific engine component,and determining the location of the leak based on the signature orrelationship. Such approach may provide the ability for proactivemaintenance, replacing reactive maintenance, and may increase thetime-in-use for assets having lubrication systems or internal combustionengines.

Non-limiting examples of such assets with internal combustion enginesinclude various vehicle types, each having its own set of operatingparameters. Embodiments disclosed herein may provide a prognosticssensor tool for early determination of leaking components via dynamicleak signatures. These sensors may be applied in multiple locations inthe engine to pinpoint the origin of leak. FIG. 57 depicts a schematicof dynamic signatures of leaks of a turbo charger (1-2 turbo chargersper engine), an intercooler (2 intercoolers per engine), a water pump (1water pump per engine), and a cylinder head (12-16 cylinder heads perengine).

FIG. 58 is a schematic diagram of a sensing system 5800 that includes asensor assembly or sensor 5802 and a device body 5804. The sensor 5802includes a sensing region 5806 that includes multiple electrodes 5808.The sensing region 5806 is configured to be placed in operationalcontact with an industrial fluid of interest, such as an oil, a fuel, ora solvent. The electrodes 5808 may contact the industrial fluid directlyor indirectly due to a dielectric layer or a sensing layer that maycover at least some of the electrodes 5808. Such sensing layer isapplied to improve detection of water or other polar compounds in anindustrial fluid. The sensing layer may be an inorganic sensing layer,unlike some conventional sensors that use polymeric sensing layers.Polymeric sensing layers in conventional resonant sensors operate byswelling and changing the resonant frequency of the sensor. In thesensor 5802, water uptake by the sensing film does not produce swellingand does not change film thickness. Rather, water uptake produces achange in the dielectric property and the capacitance of the sensingfilm at multiple frequencies. Unlike conventional resonant sensors, thesensor 5802 produces dielectric property changes of the sensing film atmultiple frequencies (produced using components illustrated in FIGS. 19and 20) that allows more accurate determinations of the contaminants,such as water or other polar compounds. Such improved accuracy isprovided by measurements of spectral dispersion of the sensing filmbefore and after fluid contamination. Non-limiting examples of watersorbing or sensing layers include porous silicon porous ceramic,anodized aluminum oxide, and others. The sensing region 5806 has anelectrode geometry that matches the measurement needs of this sensingregion 5806.

The sensor 5802 in an embodiment includes a probe body 5810 that has ashoulder 5812 extending outward from the probe body 5810 such that theshoulder 5812 has a greater radial width or diameter than the probe body5810. The shoulder 5812 is disposed along an intermediate segment of theprobe body 5810. The sensing region 5806 extends from the shoulder 5812to a distal end 5811 of the probe body 5810. A proximal end 5813 of theprobe body 5810 is operably coupled to the device body 5804. Theelectrodes 5808 are disposed on the sensing region 5806 at differentdistances relative to the shoulder 5812 such that the electrodes 5808extend different depths into the industrial fluid. In an embodiment, atleast two of the electrodes 5808 operate at one or more high frequenciesand at least one of the electrodes 5808 (that is different than theelectrodes 5808 that operate at high frequencies) operates at one ormore low frequencies.

For example, the sensor 5802 in the illustrated embodiment includesmultiple sensing sub-regions that each includes one or more electrodes5808 disposed therein. The sub-regions with electrodes each containelectrode structures where these structures are two-electrode structuresor four-electrode structures. The sensing sub-regions include a distalsensing sub-region 5808A, an intermediate sensing sub-region 5808B, anda proximal sensing sub-region 5808C. The electrodes 5808 in thedifferent intermediate sub-region 5808B are located between the distalsub-region 5808A and the proximal sub-region 5808C. The electrodes 5808in the different sub-regions 5808A-C may operate at differentfrequencies and/or frequency ranges relative to one another. Some of theelectrodes 5808 in the different sub-regions 5808A-C may be used forcontaminant (such as water) concentration detection, while otherelectrodes 5808 in the different sub-regions 5808A-C may be used fortest fluid aging detection. As an alternative to water, some examples ofother contaminants that may be detected by the sensing system 5800include fuel, dust, and other external contaminants. The electrodes 5808in the different sub-regions 5808A-C may have differing electrodespacings between adjacent electrodes 5808.

The distal sensing sub-region 5808A in an embodiment is covered by thesensing layer. The distal sensing sub-region 5808A may be configured tomeasure low concentration water or other contaminant leaks in oil. Eachelectrode 5808 in the distal sensing sub-region 5808A may be aninterdigitated electrode that has an area in the range from 0.1 mm² to100 mm². The electrode spacing for the electrodes 5808 in the sub-region5808A may be relatively small, such as in the range from 0.1 μm to 10μm. For example, the electrodes 5808 may have an area of 2 cm×2 cm withan electrode spacing of 0.15 mm. The electrodes 5808 may resonate ataround 50 MHz in air. The electrodes 5808 in the distal sub-region 5808Amay be operated at relatively high frequencies and/or frequency rangescompared to the electrodes 5808 in the intermediate and/or proximalsub-regions 5808B, 5808C.

The electrodes 5808 in the intermediate sensing sub-region 5808B arelocated more proximate to the device body 5804 than the distal sensingsub-region 5808A. The intermediate sensing sub-region 5808B is providedfor preferential measurements of leaks of nonpolar external contaminantsand fluid aging detection. These electrodes 5808 in an embodiment arenot coated with a sensing layer. The electrodes 5808 in the intermediatesub-region 5808B may have relatively small spacing in the range from 0.1μm to 10 μm. The electrodes 5808 of the intermediate sub-region 5808Bmay be operated at relatively high frequencies and/or frequency rangescompared to the electrodes 5808 in the proximal sub-region 5808C.

The electrodes 5808 in the proximal sensing sub-region 5808C aredisposed more proximate to the device body 5804 than the sensingsub-regions 5808A and 5808B. The electrodes 5808 in the sub-region 5808Care provided for preferential measurements of fluid aging detection.These electrodes are not coated with a sensing layer and can haverelatively large spacing in the range from 1 μm to 5000 μm. Theelectrodes 5808 of the proximal sub-region 5808B may be operated atrelatively lower frequencies and/or frequency ranges compared to theelectrodes 5808 in the distal and/or intermediate sub-regions 5808A,5808B.

With additional reference to FIGS. 19 and 20, the sensor 5802 includesat least one resonant inductor-capacitor-resistor (LCR) circuit havingone or more tuning elements 1942. The one or more resonant LCR circuitsare configured to generate an electrical stimulus having a spectralfrequency range. The electrical stimulus is applied to the industrialfluid at the sensing region 5806 via the electrodes 5808.

The sensor 5802 is operably coupled to the device body 5804, such as viaa mechanical fixed connection, a wired connection, or a wirelesselectrical connection. The device body 5804 may be the device body 315shown in FIG. 7. For example, the sensor 5802 may include acommunication unit (e.g., a transceiver or discrete transmitter andreceiver) that wirelessly transmits electrical signals to the devicebody 5804. The device body 5804 includes one or more processors, whichmay be or include the processing unit 306 shown in FIG. 7. The one ormore processors are configured to receive an electrical signal from thesensor 5802 that is representative of a resonant spectral response (orresonant impedance spectra) of the sensing region in operational contactwith the industrial fluid in response to the electrical stimulus beingapplied to the industrial fluid.

The one or more processors are configured to analyze the resonantspectral response and determine both a water concentration in theindustrial fluid and an aging level of the industrial fluid based on theanalyzed resonant spectral response. The resonant spectral response isindicative of a dielectric dispersion profile of the industrial fluidover the spectra frequency range of the electrical stimulus. The one ormore processors may be configured to analyze the resonant spectralresponse by extracting complex resonance parameters from the resonantspectral response. The complex resonance parameters are described withreference to FIGS. 23 and 29. The concentration of water or otherexternal contaminants in the industrial fluid and the aging level of thefluid may be determined by comparing the extracted complex resonanceparameters to known resonance parameters associated with various waterconcentrations of the industrial fluid and various aging levels of theindustrial fluid. The comparison may include classifying the extractedresonance parameters using an earlier built classification model (asdescribed in steps 2870 and 2872 of FIG. 29) and quantitating theextracted resonance parameters using an earlier built classificationmodel (as described in steps 2880 and 2882 of FIG. 29).

In an embodiment, the sensor 5802 includes multiple resonant LCRcircuits. Each resonant LCR circuit has a different resonant frequency.The electrical stimulus applied to the industrial fluid is generatedover a spectral frequency range that includes or incorporates theresonant frequencies of the resonant LCR circuits such that theimpedance spectral response is measured over the resonant frequencies.Optionally, the sensor 5802 may include a multiplexer 1944 (shown inFIG. 19) that is configured to individually control the resonant LCRcircuits to tune the electrical stimulus that is applied to theindustrial fluid. The multiple resonant frequencies allow the sensingsystem 5800 to detect multiple variables or properties of the industrialfluid, such as the concentration of water and the age of the fluid. Forexample, the sensing system 5800 may include four resonant frequencies.

The sensor 5802 may also include data acquisition circuitry (not shown)which may be similar to the data acquisition circuitry 1716 shown inFIGS. 17 and 18. The data acquisition circuitry is configured togenerate an electrical signal representative of the measured resonantimpedance spectra. The electrical signal may be transmitted to aprocessing device, such as the device body 5804, for analysis of theresonant impedance spectra to determine one or more properties of theindustrial fluid. The one or more properties in an exemplary embodimentare both a concentration of water (or another external contaminant) inthe fluid and an aging level of the fluid.

The analysis of the resonant impedance spectra may be performed bycomparing the extracting resonance parameters from the measured resonantimpedance spectra from the electrodes in each of the sensing sub-regions5808A, 5808B, and 5808C to known resonance parameters of the same or asimilar fluid at various defined concentrations of water in the fluid orother external contaminant and at various age levels of the fluid. Inone example in which water is the external contaminant, the tested fluidof interest may be determined to have a given water concentration and agiven age level responsive to the measured set of resonance parametersmatching a set of known resonance parameters associated with the givenwater concentration and the given age level to a greater extent than themeasured set of resonance parameters matches other sets of knownresonance parameters associated with other concentrations of waterand/or age levels. Statistical methods may be used to compare and“match” the measured resonance parameters to the known resonanceparameters. The statistical method used may be a regression analysis,such as a linear regression, a nonlinear regression, or the like. Inanother example, a series of experiments may be performed using a singlesensor to determine the measured resonance parameters of a resonantimpedance spectral response of the sensor in a given industrial fluid atvarious concentrations of water or other external contaminant in thefluid and at various age levels of the fluid, which are the two or morevariables that change across the series of experiments. The measuredresonance parameters for the series of experiments may be plotted asdata points on a graph, and may be used to develop a quantitative modelthat is used to predict the water or other external contaminantconcentration and the age level of monitored fluids (where the waterconcentration or other external contaminant and the age are unknown).The quantitative model may be a transfer function for the sensing region5808 broadly or for the individual sensing sub-regions 5808A, 5808B, and5808C. Thus, measured resonance parameters from a resonance impedancespectral response may be input as variables into the quantitative modelto predict water or other external contaminant concentration and aginglevel of the tested fluid.

The determination of the contaminant concentration in and/or age of thefluid of interest may be performed by establishing correlations betweenthe spectral responses of the sensing sub-regions 5808A, 5808B, and5808C at multiple frequencies across the dispersion profiles of thecontaminant concentration and/or the age of the fluid and the levels ofthe contaminant concentration and/or the age of the fluid as determinedinitially via independent reference laboratory methods. Once thesecorrelations (also known as transfer functions) are established, theyare further utilized to predict the unknown measured concentrations.Such predictions may be performed by having the measured signals fromthe sensing sub-regions 5808A, 5808B, and 5808C at multiple frequenciesacross the dispersion profiles of the contaminant concentration and/orthe age of the fluid, entering the values of these signals into thetransfer functions or a single function, and obtaining the predictedvalues of the contaminant concentration and/or the age of the fluid.Depending on the transfer functions, one or more contaminants may bequantified from the measured signals from the sensing sub-regions 5808A,5808B, and 5808C at multiple frequencies across the dispersion profilesof the contaminants concentration and/or the age of the fluid.

The concentrations of water or other external contaminants detected bythe sensor 5802 may be down to 1 ppm. FIG. 59 depicts responses of thisdeveloped resonant sensor 5802 to water leaks into engine oil at levelsof 25 ppm, 25 ppm, and 50 ppm each. The water levels indicate additionsof water, so the second addition of water at 25 ppm results in doublingthe amount of water added to the sample fluid, and the third leak levelresults in four times the concentration of water relative to the firstleak level. The data in FIG. 59 illustrates that this sensor 5802 maydetect the water leaks at the lowest tested level of 25 ppm with highsignal-to-noise ratio quality, resulting in the ability to resolve 1 ppmof water leak with a signal-to-noise (S/N) ratio of 3.

The performance of this developed resonant sensor may be compared withthe performance of a standard non-resonant capacitance sensor that isused as a reference capacitance sensor. The comparison may be performedby having both sensors in the same circulating-oil loop where waterleaks may be introduced and presented to both sensors. Water leak levelsmay be 25 ppm, 25 ppm, and 50 ppm each. FIG. 60 depicts the response ofthe reference capacitance sensor to water leaks into engine oil atlevels of 25 ppm, 25 ppm, and 50 ppm each. This figure illustrates thatthe reference capacitance sensor did not show an appreciable signalchange due to noise, indicating an inability to distinguish among thedifferent concentrations of water leaks.

Benchmarking of the multivariable resonant sensor 5802 may be performedin comparison to a control or reference tuning fork sensor forquantitation of water leaks into oil. The tuning fork sensor is amechanical resonator sensor that measures viscosity, density anddielectric constant of a test fluid. The benchmarking was performed byhaving both sensors in the same circulating-oil loop where water leakswere introduced and presented to both sensors. Water leaks levels wereinduced at 50-ppm steps. FIG. 61 shows the response of the multivariableresonant sensor to water leaks into engine oil responsive to the 50 ppmsteps. FIG. 61 indicates that the sensor 5802 detects water leaks with ahigh signal-to-noise ratio. FIG. 62 depicts the response of the controltuning fork sensor to water leaks into engine oil at 50 ppm steps. Thedata in FIG. 62 demonstrates a significantly lower signal-to-noise ratiofor the control tuning fork sensor relative to the sensor 5802.

In an experimental example, quantitation of water leaks at variousstages of oil aging was performed using the sensor of one or more of theembodiments disclosed herein. The industrial fluid was automotive oil10W-30. Water was added into the oil at different levels ranging from 25parts per million (ppm) to 900 ppm when oil had three different aginglevels. The aging levels were fresh (0% aging), old (100% aging), andintermediate (50% aging). The fresh oil indicates new oil, the old oilindicates oil with a mileage of 5000 miles in an automotive, and theintermediate oil is a 50/50 ratio of fresh and old oil. The oil may beconsidered new or fresh at or proximate to a beginning of a recommendedfluid life of the oil, the oil may be considered old at or proximate toan end of the recommended fluid life of the oil, and the oil may beconsidered intermediate at or proximate to the middle of the recommendedfluid life. For example, for an oil with a recommended fluid life of5000 miles in a vehicle, the oil may be considered as new or freshduring the first 10% of the recommended fluid life (e.g., during roughlythe first 500 miles), the oil may be considered as old for the last 10%of the recommended life (e.g., during roughly the final 500 miles beforereaching 5000 miles) and during any additional miles beyond therecommended life, and the oil may be considered as intermediate for themiddle 10% of the recommended life (e.g., during the period roughlybetween miles 2250 and 2750).

FIG. 63 is a plot depicting the raw responses of the resonanceparameters (e.g., F1, F2, Fp, Z1, Z2, and Zp) of the resonant impedancespectra measured by the sensor 5802 (shown in FIG. 58). As shown in FIG.63, the sensor 5802 responds differently to the water additionsdepending on the aging levels of the oil samples. A quadratic transferfunction was developed based on the raw data obtained in the experimentin order to predict water leaks into the oil. The results of thepredicted versus actual concentrations are presented in FIGS. 64 and 65.FIG. 64 shows the results of the predicted versus actual concentrationsfor individual different levels of aging, and FIG. 65 shows acorrelation plot between the actual and predicted water concentrationsfor the three levels of oil aging (e.g., beginning of a recommended oillife, middle of the recommended oil life, or end of the recommended oillife). The solid plot line represents a quantitative curve or modeldeveloped based on a series of experiments using known waterconcentrations in the oil and known age levels of the oil. The circulardata points represent predicted water concentrations and age levelsbased on resonance parameters extracted or calculated from measuredresonant impedance spectral responses of the sensor in contact withfluids of unknown water concentration and unknown age. These resultsdemonstrate that the single developed multivariable sensor discriminateswell between water leaks and oil aging and provides the ability topredict water concentrations. FIG. 66 is a correlation plot betweenactual and predicted oil aging using the sensor, which indicates thatthe single developed multivariable sensor also discriminates wellbetween oil aging levels and provides the ability to predict oil aging.As a result, the single sensor is able to predict with significantaccuracy both the concentration of water in the industrial fluid and theage of the fluid (relative to a recommended fluid life) without the needfor multiple sensors to obtain such information.

A similar experiment was performed using a conventional capacitancesensor using the same oil and the same water concentrations and aginglevels. The results of the experiment indicate that the conventionalcapacitance sensor does not discriminate between water leaks and oilaging. The conventional capacitance sensor is not able to predict waterconcentrations at more than one aging level. Measurements were performedsimultaneously with the conventional capacitance sensor and themultivariable resonant sensor (e.g., such as the sensor 5802 shown inFIG. 58). FIG. 67 depicts the raw response of the conventionalcapacitance sensor to water additions into differently aged oil samples.The capacitance sensor responded significantly to differently aged oilsamples and less to the water additions into oil. A quadratic transferfunction was developed to predict water leaks into fresh oil. Results ofthe predicted vs actual concentrations of water concentrations forindividual different levels of aging measured with a conventionalcapacitance sensor are presented in FIG. 68. These results demonstratethat a conventional capacitance sensor does not discriminate betweenwater leaks and oil aging and only provides the ability to predict waterconcentrations in fresh oil.

The performance of the developed multivariable resonant sensor wasfurther benchmarked with the tuning fork sensor in quantitation of waterleaks into oil at various stages of oil aging at one temperature. Theemployed model oil was automotive oil 10W-30 (AutoZone). Water wasspiked into oil at 50-ppm levels providing steps of 50, 100, 150, 200,and 250 ppm of total water additions when oil had three levels of agingsuch as 50, 70, and 100%. FIG. 69 depicts raw responses of (A) F_(p),F₁, F₂ and (B) Z_(p), Z₁, Z₂ of the multivariable resonant sensor towater additions into differently aged oil samples. The data pointscorresponding to three levels of aging were from 0 to 30 (aging 50%),from 31 to 60 (aging 70%), and from 61 to 90 (aging 100%). The mileagefor aged oil was 5000 miles. The 0% aging was fresh oil; the 100% wasoil aged at 5000 miles; the 50% and 70% were 50/50 and 70/30 ratios offresh and aged oil. The multivariable resonant sensor respondeddifferently to the water additions into differently aged oil samples.

As a benchmark, quantitation of water leaks at various stages of oilaging was performed using the tuning fork. Measurements were performedsimultaneously with the tuning fork and the multivariable resonantsensor (e.g., such as the sensor 5802 shown in FIG. 58). FIGS. 70A-Cdepict the raw dielectric constant, density, and viscosity outputs,respectively, of the tuning fork sensor. The tuning fork sensorresponded strongly to differently aged oil samples and relatively muchless to the water additions into oil as depicted in FIG. 70A. Responseof the tuning fork to oil aging was dominating over the response towater leaks. In particular, dielectric constant response (FIG. 70A)showed strong response to aging (signal jumps at 30 and 60 points) andonly relatively small effect of water leaks (small slopes of responseover 0-30, 31-60, and 61-90 data points. The density (FIG. 70B) andviscosity (FIG. 70C) outputs showed only responses to aging.

Water leaks and oil aging levels were attempted to be quantified usingthe multivariable resonant sensor (e.g., the sensor 5802 shown in FIG.58) and the conventional tuning fork sensor. Transfer functions wereconstructed for each sensor based on their respective outputs. Thetransfer functions were used to predict water leaks and oil aginglevels. The residual prediction errors were evaluated by subtractingactual and predicted values of water leaks and oil aging. FIG. 71 showsthe results of predicted and actual concentrations of water leaks intooil for the multivariable resonant sensor at different oil aging levels.These results demonstrate that a single developed multivariable sensorprovided the ability to predict water concentrations, as illustrated bythe close positioning of predicted values (open circles) to the actualvalues (solid line) in FIG. 71. FIG. 72 shows the results of predictedand actual concentrations of water leaks into oil for the conventionaltuning fork sensor at different oil aging levels. These resultsdemonstrate that the tuning fork sensor was unable to predict waterconcentrations in oil of different aging levels, as illustrated by theseemingly random scatter of predicted values (open circles) to theactual values (solid line) in FIG. 72.

To determine positions of resonances in the multi-resonant sensor,dielectric properties of fresh and aged oil samples in a broad range offrequencies from 100 Hz to 10 MHz were measured using a dielectricspectroscopy setup consisting of an Agilent 4294A precision impedanceanalyzer and an Agilent 16452A liquid test fixture. Dielectric spectrawere transferred from the 4294A impedance analyzer to a data processingcomputer using a 4294A data transfer program available from Agilent as aMicrosoft Excel macro and was analyzed as described in the 16452A testfixture manual to obtain the real and imaginary parts of the complexdielectric constant (∈′ and ∈″, respectively). These measurements wereused in the determination of the spectral dispersion properties of oilsand allowed the further downselection of operating frequencies for themulti-resonance sensor operation.

FIGS. 73A and 73B depict an application of the multiresonant sensorsystem for the correction for oil aging that shows one example of theselection of operating frequencies of the multiresonant sensor systemacross the spectral dispersions shown for a range of fresh and used(aged) locomotive oils. FIG. 73A is the real part (∈′) and FIG. 73B isthe imaginary part (∈″) of the complex dielectric constant of alocomotive oil. Arrows and dotted lines indicate initially selectedregions for the multiresonant sensor operation. The real and theimaginary portions of the complex permittivity are depicted with theinitially selected regions for the multiresonant sensor operation. Theseregions are selected based on the dispersion of ∈′ and ∈″ to capturespectral trends upon oil aging. FIGS. 74A and 74B depict the real andthe imaginary portions of the complex permittivity of the employed modelautomotive oil 10W-30 with three levels of aging such as 0, 50, and 100%and illustrates trends of ∈′ and ∈″ upon oil aging, which is attractivefor the selection of operating frequencies of the multiresonant sensorsystem. Arrows and dotted lines indicate initially selected regions forthe multiresonant sensor operation.

In another experimental example, water leaks into oil were studiedduring the operation of a helicopter engine. The helicopter engine was aturboshaft CT7 helicopter engine made by GE. Water in the form of anemulsion was added to the oil sump prior to the engine start. Ahomogenizer was used to emulsify water with the CT7 engine oil. First,the loss of water in the oil during the helicopter engine operation wasstudied with the near-infrared spectroscopy using a Cary 500i UV-vis-NIRspectrophotometer (Varian, Inc., Santa Clara, Calif.) using quartzcuvettes with a 1-cm path length. Initially, oil samples with knownamounts of water were measured to establish the relationship betweennear-infrared absorbance and water content. Next, samples were takenbetween the runs of the helicopter engine and analyzed withnear-infrared spectroscopy for the presence of residual water. The 500ppm water was added to the sump of the engine, and then the engine wasallowed to run for specified time periods in the ground idle mode. Oilsamples were taken between the runs and analyzed with near-infraredspectroscopy for the presence of residual water. The water presence wasdeduced from the characteristic water absorption band at 1900 nm afterthe measurement setup calibration with oil-water mixtures with the knownwater content. The results indicated that for a given concentration of500 ppm water, water was completely eliminated from the oil in aroundfive minutes on the ground idle. Thus, the water signature could bedetected within the first few minutes after the engine start.

Detection of water concentrations in a turboshaft helicopter engine wasfurther performed using the multivariable resonant sensor (e.g., such asthe sensor 5802 shown in FIG. 58). The 4-cm² 100-μm-IDE-spacing sensoroperating at around 38 MHz (in oil) was placed inside a 1-inchT-connector that was a part of a specially installed ⅜″ OD bypass oilline connected to the engine to ensure oil flow through the sensorduring the engine operation. Benchmarking of the performance of themultivariable resonant sensor was done by comparison with a conventionaltuning fork sensor, installed sequentially. Measurements of water leakswere performed by adding water concentrations of 1000, 3000, and 5000ppm and observing dynamic response patterns. Results of theseexperiments are summarized in FIG. 75A, which shows the results oftriplicate runs with for the engine warm-up, baseline (no added water),and water additions of 1000, 3000, and 5000 ppm. The correlation betweenthe sensor response and added water concentration was established bymeasuring sensor response after 1.5 min upon water addition, as shown inFIG. 75B.

FIGS. 76A and 76B show responses of the installed multivariable resonantsensor and the tuning fork sensor, respectively, upon testing of engineoil of the turboshaft helicopter with an added 5000 ppm of water andobserving dynamic response patterns. The tuning fork sensor responseshown in FIG. 76B was corrected for the temperature fluctuation duringthe measurement. The estimated the signal-to-noise ratio of both sensorswas taken at their maxima, and the noise levels were taken upon waterevaporation at stable response regions during individual runs. As shownin FIG. 76A, the signal-to-noise ratio of the multivariable resonantsensor was in the range of generally 230-525. As shown in FIG. 76B, thesignal-to-noise ratio of the tuning fork sensor was in the range ofgenerally 25-60. In FIG. 76B, the dielectric constant increases with theaddition of water.

Using an approach of selecting the appropriate frequency ranges asdepicted in FIGS. 73A and 73B and FIGS. 74A and 74B, four types ofautomotive oil were measured with different levels of added water atconcentrations of 0 ppm, 1000 ppm, 2000 ppm, and 3000 ppm. The differenttypes of automotive oil were 0W-20, 10W-30, 15W-40, and SAE30. FIG. 77illustrates results of predicted water concentrations versus actualwater concentrations in different types of oils using a single transferfunction. The data in FIG. 77 illustrates the ability of the developedsensing methodology to detect and quantify an external contaminant suchas water into diverse types of oil without effects of the type of oil.

A sensor of the disclosure may analyze an industrial fluid such as gasdissolved in oil or ambient air at an industrial site. Detection ofmethane and other gases may be performed using metal oxide sensors. Ametal oxide sensor changes its resistance signal in relation to gasconcentration. Unfortunately, it is well accepted that at relativelyhigh concentrations of gases, the resistance signal of the metal oxidesensor saturates or even changes its direction of the response. Thus,over relatively large concentrations of gases, the resistance signal ofthe metal oxide sensors may be non-linear and even non-monotonic. Whensuch a metal oxide sensor was connected to an LCR resonator to operatein a resonant mode as depicted in FIG. 22, measurements of resonantproperties (such as the parameters shown in FIG. 23) of the sensor weredetermined. The metal oxide sensor was exposed to three sets of methanegas concentrations. Each set of methane gas concentrations was presentedtwice to the sensor thus providing two replicate measurements per eachset of methane gas concentrations. Methane concentrations were asfollows:

Set #1: 0, 102, 306, 510, 714, 918, 1122, 1327, 1531, and 1735 ppm.

Set #2: 0, 172, 517, 862, 1207, 1552, 1897, 2241, 2586, and 2931 ppm.

Set #3: 0, 263, 789, 1316, 1842, 2368, 2895, 3421, 3947, and 4474 ppm.

These gas concentrations were produced by diluting methane concentrationof 10000 ppm available from a gas tank with air at different ratios ofmethane-to-air. These different ratios were provided by variable totalflow of gas delivered to the sensor. To generate the Set #1 of methaneconcentrations, the total gas flow was relatively large as compared tothe total gas flow needed to generate the Set #2 and Set #3 of methaneconcentrations. In this experiment, exposures of the sensor to differentmethane concentrations were performed for about 2 minutes and werealternated with exposures to blank clean carrier gas without methane forabout 2 minutes. The time between replicates from the same set was about14 minutes. The time between different sets was about 22 minutes.

FIG. 78 depicts the Zp and Fp responses of the resonant metal oxidesensor, where Zp is resistance change of the sensor and Fp is frequencypeak position of the sensor. The responses Zp and Fp of the sensor werecompletely reversible upon periodic exposures of the sensor to methanefollowed by the exposures to blank clean carrier gas without methane.For example, as shown in FIG. 78 over the time from 0 to 20 min, Zpresponse to blank clean carrier gas is about 900 Ohm, and Fp response toblank clean carrier gas is about 24.68 MHz. The first exposure of thesensor to methane concentration of 102 ppm at about 20 min for 2 minutes(Set #1, replicate 1) produced Zp signal change from about 900 Ohm toabout 700 Ohm and Fp signal change from about 24.68 MHz about 24.75 MHz.Overall, Zp and Fp responses of sensor produced nine well-resolved stepsupon exposure to methane per every replicate of sets 1-3. Linearity ofZp and Fp responses as a function of methane concentration is observableby comparing the magnitudes of Zp and Fp responses at different methaneconcentrations. At the methane gas concentrations of Set #1 above, theresistance signal response Zp of the resonant metal oxide becomesnonlinear at the high methane concentrations. At the methane gasconcentrations of Set #2, the resistance signal response Zp of theresonant metal oxide becomes saturated at the high methaneconcentrations. At the methane gas concentrations of Set #3, theresistance signal response of the resonant metal oxide changes itsdirection at the high methane concentrations. Thus, the resistancesignal responses Zp in all three sets are generally non-linear withrespect to methane concentration. Further, there are steps in thebaseline response of the sensor upon changes of the flow conditions fromSet #1 to Set #2 and to Set #3.

As shown in FIG. 78, the frequency peak position response Fp of theresonant metal oxide sensor has a significant linearity with respect tomethane concentration. For example, the frequency peak position Fp(represented as the peaks of the plot line) signal response of theresonant metal oxide sensor increases generally linearly as theconcentration of methane increases in each set. At the methane gasconcentrations of Set #1 and Set #2, Fp signal response of the resonantmetal oxide is linear at all such concentrations, but the Fp signalresponse at the concentrations of Set #3 is slightly nonlinear at thehigh methane concentrations. Further, there are no noticeable steps inthe baseline response of the sensor upon changes of the flow conditionsfrom Set #1 to Set #2 and to Set #3. Thus, the application of a metaloxide sensor in a resonant mode as a part of the LCR circuit providesthe advantages of having a linear frequency peak position Fp response ofthe sensor to gas concentrations and having a stable baseline. The Fpresponse of the sensor is directly related to the change in thecapacitance of the sensor. Change in capacitance of described methanesensor may be measured using a resonant or non-resonant readout. Asshown in FIG. 78, a linear progression of Fp response as a function ofmethane concentration was observed. A nonlinear progression of Zpresponse as a function of methane concentration was observed.

FIG. 79 is a flow chart representative of a method 6300 for determiningmultiple properties of an industrial fluid. At 6302, an electrical orelectromagnetic stimulus is applied to an industrial fluid using asensor. The “electrical stimulus” may additionally or alternatively bean electromagnetic stimulus. The sensor includes at least one resonantinductor-capacitor-resistor (LCR) circuit configured to generate theelectrical stimulus. The electrical or electromagnetic stimulus isapplied to the industrial fluid via multiple electrodes at a sensingregion of the sensor in operational contact with the industrial fluid.Optionally, the sensor may include multiple LCR circuits that havedifferent resonant frequencies. Applying the electrical orelectromagnetic stimulus to the industrial fluid may include generatingthe electrical or electromagnetic stimulus to incorporate the resonantfrequencies of the resonant LCR circuits such that the resonantimpedance spectral response is measured over the resonant frequencies ofthe resonant LCR circuits. The method 6300 may also include tuning theelectrical or electromagnetic stimulus generated by the at least one LCRcircuit using one or more tuning elements. The tuning elements mayinclude one or more inductors, capacitors, resistors, resonators, orimpedance transformers.

At 6304, an electrical or electromagnetic signal is received from thesensor. The electrical or electromagnetic signal is representative of aresonant impedance spectral response of the sensing region inoperational contact with the industrial fluid in response to theelectrical or electromagnetic stimulus being applied to the industrialfluid. At 6306, the resonant impedance spectral response is analyzed todetermine both a water concentration in the industrial fluid and anaging level of the industrial fluid based on the analyzed resonantimpedance spectra. Although “water concentration” is mentioned, in otherembodiments the concentration may be of another external contaminantother than water. The water or other external contaminant concentrationin the industrial fluid and the aging level of the industrial fluid maybe determined by comparing the extracted complex resonance parameters toknown resonance parameters associated with various water or otherexternal contaminant concentrations in the industrial fluid and variousaging levels of the industrial fluid. The aging level of the fluid isdetermined by categorizing the fluid as three levels as one of fresh,old, or intermediate. The aging level of the fluid may be alsodetermined by categorizing the fluid with more levels of aging where thenumber of levels of aging may be 8, 64, 128, 256, 512, 1024, 2048, 4096,65536 or more. The number of aging levels determined by the sensor maydepend on the developed transfer function between fluid aging andmultivariable sensor response.

The determination of oil aging by levels is important for differentapplications. For example a two-level aging of oil means that level 1 isa fresh oil and level 2 is aged oil that requires oil replacement orsome other action. The higher number of resolution levels of oil aging,the more accurate performed actions can be, including prognosticalgorithms to predict the remaining life of oil and/or the machine or anindustrial system or site.

Analyzing the resonant impedance spectra may include extracting complexresonance parameters of the resonant impedance spectra. The complexresonance parameters are at least some of a frequency position (Fp) andmagnitude (Zp) of a real part of the resonant impedance spectra, aresonant frequency (F1) and antiresonant frequency (F2) of an imaginarypart of the resonant impedance spectra, an impedance magnitude (Z1) atthe resonant frequency (F1) and an impedance magnitude (Z2) at theantiresonant frequency (F2), and a zero-reactance frequency (Fz) at theimaginary part of the resonant impedance spectra.

In an embodiment, a system includes a sensor and a device body. Thesensor includes a sensing region and at least one resonantinductor-capacitor-resistor (LCR) circuit. The sensing region includesat least two electrode structures. The sensing region of the sensor isconfigured to be placed in operational contact with an industrial fluidof interest. The at least one resonant LCR circuit is electricallyconnected to the electrode structures and configured to generate anelectrical stimulus having a spectral frequency range. The electricalstimulus is applied to the industrial fluid via the electrodestructures. The device body is operably coupled to the sensor. Thedevice body includes one or more processors configured to receive anelectrical signal from the sensor. The electrical signal isrepresentative of a resonant impedance spectral response of the sensingregion in operational contact with the industrial fluid in response tothe electrical stimulus being applied to the industrial fluid. The oneor more processors are further configured to analyze the resonantimpedance spectral response and determine both a water concentration inthe industrial fluid and an aging level of the industrial fluid based onthe resonant impedance spectral response that is analyzed.

In one example, industrial fluid is lubricant, fuel, hydraulic media,drive fluid, power steering fluid, solvent, power brake fluid, drillingfluid, oil, crude oil, heat transfer fluid, insulating fluid, compressedair, ambient air on an industrial site or structure, water, naturallyoccurring fluid, synthetic fluid.

In one example, industrial fluid is lubricating oil with known type andlevel of additives designed for their applications under differentenvironmental conditions and with different wear protection, anddifferent particles-deposit control.

In one example, the sensing region of the sensor is configured to bedisposed within a reservoir of a machine having moving parts that arelubricated by the industrial fluid in the reservoir.

In one example, each resonant LCR circuit includes one or more tuningelements. The one or more tuning elements comprise one or moreinductors, capacitors, resistors, resonators, or impedance transformers.

In one example, the sensor includes multiple resonant LCR circuits thathave different resonant frequencies. The spectral frequency range of theelectrical stimulus is applied to the industrial fluid incorporating theresonant frequencies of the resonant LCR circuits such that the resonantimpedance spectral response is measured over the resonant frequencies ofthe resonant LCR circuits. Optionally, the sensor includes a multiplexerthat is configured to individually control the resonant LCR circuits totune the electrical stimulus that is applied to the industrial fluid.

In one example, the industrial fluid of interest is at least one of anoil, a fuel, a solvent, solid, or ambient air at an industrial site.Non-limiting examples of an industrial site include manufacturingfacility, processing facility, disposal facility, industrial researchfacility, gas producing facility, oil producing facility, and others.

In one example, the one or more processors are configured to analyze theresonant impedance spectral response by extracting complex resonanceparameters of the resonant impedance spectral response. The one or moreprocessors are configured to determine the concentration of water orother external contaminant in the industrial fluid and the aging levelof the industrial fluid by comparing the extracted complex resonanceparameters to known resonance parameters associated with various waterconcentrations and aging levels. Optionally, the complex resonanceparameters include one or more of a frequency position (Fp) andmagnitude (Zp) of a real part of the resonant impedance spectra, aresonant frequency (F1) and antiresonant frequency (F2) of an imaginarypart of the resonant impedance spectra, an impedance magnitude (Z1) atthe resonant frequency (F1) and an impedance magnitude (Z2) at theantiresonant frequency (F2), or a zero-reactance frequency (Fz) at theimaginary part of the resonant impedance spectra.

In one example, the one or more processors are configured to determinethe aging level of the industrial fluid as being at or proximate to abeginning of a recommended fluid life, at or proximate to a middle ofthe recommended fluid life, or at or proximate to an end of therecommended fluid life.

In one example, the sensor has a probe body that extends between adistal end and a proximal end. The probe body includes a shoulderdisposed between the distal end and the proximal end. The sensing regionof the sensor extends from the shoulder to the distal end of the probebody. The electrode structures of the sensing region are disposed atdifferent distances relative to the shoulder such that the electrodestructures extend different depths into the industrial fluid.

In one example, at least one of the electrode structures of the sensingregion operates at higher frequencies than at least one other electrodestructure of the electrode structures.

In one example, at least one of the electrode structures of the sensingregion includes electrodes coated with at least one of a protectivelayer or a sensing layer and at least another of the electrodestructures includes bare electrodes.

In one example, the multivariable sensor has electrodes of the sensingregion that are coated with a sensing layer where the electrodes and thesensing layer operate at an elevated temperature ranging from about 100degrees Celsius to about 1600 degrees Celsius.

In an embodiment, a method includes applying an electrical stimulus toan industrial fluid using a sensor. The sensor includes at least oneresonant inductor-capacitor-resistor (LCR) circuit configured togenerate the electrical stimulus. The electrical stimulus is applied tothe industrial fluid via at least two electrode structures at a sensingregion of the sensor in operational contact with the industrial fluid.The method also includes receiving an electrical signal from the sensorrepresentative of a resonant impedance spectral response of the sensingregion in operational contact with the industrial fluid in response tothe electrical stimulus being applied to the industrial fluid. Themethod further includes analyzing the resonant impedance spectralresponse to determine both a water concentration in the industrial fluidand an aging level of the industrial fluid based on the resonantimpedance spectra that is analyzed. The stimulus may be electrical orelectromagnetic stimulus.

In one example, analyzing the resonant impedance spectral responseincludes extracting complex resonance parameters of the resonantimpedance spectral response. The complex resonance parameters are one ormore of a frequency position (Fp) and magnitude (Zp) of a real part ofthe resonant impedance spectra, a resonant frequency (F1) andantiresonant frequency (F2) of an imaginary part of the resonantimpedance spectra, an impedance magnitude (Z1) at the resonant frequency(F1) and an impedance magnitude (Z2) at the antiresonant frequency (F2),or a zero-reactance frequency (Fz) at the imaginary part of the resonantimpedance spectral response. Optionally, the water concentration in theindustrial fluid and the aging level of the industrial fluid aredetermined by comparing the extracted complex resonance parameters toknown resonance parameters associated with various water concentrationsin the industrial fluid and various aging levels of the industrialfluid. Water is one of exemplary external contaminants. Additionalnon-limiting examples of external contaminants fuel, dust, metal wearparticles, coolant, debris, and others.

In one example, the sensor that applies the electrical stimulus to theindustrial fluid is a metal oxide sensor.

In one example, the method further includes tuning the electricalstimulus generated by the at least one resonant LCR circuit using one ormore tuning elements. The one or more tuning elements include one ormore inductors, capacitors, resistors, resonators, or impedancetransformers.

In one example, analyzing the resonant impedance spectral response todetermine the aging level of the industrial fluid includes categorizingthe industrial fluid as being at or proximate to a beginning of arecommended fluid life, at or proximate to a middle of the recommendedfluid life, or at or proximate to an end of the recommended fluid life.

In one example, the sensor includes multiple resonant LCR circuits thathave different resonant frequencies. Applying the electrical stimulus tothe industrial fluid includes generating the electrical stimulus toincorporate the resonant frequencies of the resonant LCR circuits suchthat the resonant impedance spectral response is measured over theresonant frequencies of the resonant LCR circuits.

In an embodiment, a system for monitoring a condition of an industrialsite includes a sensor and a device body operably coupled to the sensor.The sensor has at least two sufficiently non-correlated output signalsrepresentative of a response of the sensor to an industrial fluid at theindustrial site. The device body includes one or more processorsconfigured to receive the output signals from the sensor and analyze theoutput signals to determine both a concentration of an externalcontaminant in the industrial fluid and an aging level of the industrialfluid based on the output signals.

In one example, the condition of the industrial site is based on theconcentration of the external contaminant in the industrial fluid andthe aging level of the industrial fluid.

In one example, the industrial site is at least one of a first machinethat has moving parts, a second machine that does not have movableparts, a manufacturing facility, a processing facility, a disposalfacility, an industrial research facility, a gas producing facility, oran oil producing facility.

In one example, the industrial fluid is at least one of a lubricant, afuel, a hydraulic media, a drive fluid, a power steering fluid, asolvent, a power brake fluid, a drilling fluid, an oil, an insulatingfluid, a heat transfer fluid, compressed air, ambient air, water, anaturally occurring fluid, or a synthetic fluid.

In one example, the industrial fluid is a lubricating oil with knowntype and level of additives designed for exposure to multipleenvironmental conditions and with different wear protection anddifferent particles-deposit control.

In one example, the sensor is a metal oxide sensor.

In one example, the output signals of the sensor represent a resonantimpedance spectral response of the sensor in operational contact withthe industrial fluid responsive to an electrical stimulus being appliedto the industrial fluid. The one or more processors of the device bodyare configured to analyze the output signals by extracting complexresonance parameters of the resonant impedance spectral response. Thecomplex resonance parameters include a frequency position of a real partof the resonant impedance spectral response. The frequency positionincreases linearly with increasing concentration of the externalcontaminant.

In one example, one of the two sufficiently non-correlated outputsignals represents an impedance response of the sensor to the industrialfluid. The other of the two sufficiently non-correlated output signalsrepresents a capacitance response of the sensor to the industrial fluid.

FIG. 80 illustrates another embodiment of a sensor assembly 8000. Thesensor assembly 8000 may represent one or more embodiments of the sensoror sensor assemblies 1714, 1940, 5802 described herein, and may beincluded in one or more of the sensor systems described herein. Thesensor assembly 8000 is placed into contact with an industrial fluid ofinterest, such as oil, fuel, solvent, etc.

The sensing region 8004 may include electrodes, as described above. Thesensing region 8004 of the sensor assembly 8000 is placed into contactwith an industrial fluid 8006. The electrodes can generate an electricfield of one or more frequencies to excite the fluid 8006 and/or sensingregion 8004. The sensing region 8004 includes an electrical,non-resonant and/or resonant circuit that can operate at one or morenon-harmonic and non-resonant or resonant frequencies. A sensor reader8008 is located inside the sensor body 8002, and may include one or moreprocessors (e.g., application specific integrated circuits, fieldprogrammable gate arrays, microprocessors, etc.). The sensor reader 8008can represent the sensor reader 106. In one embodiment, the sensorreader 8008 can include an application specific integrated circuitavailable from Analog Devices (Model AD5933).

The sensor reader 8008 measures the response of the sensing region 8004during excitation of the sensing region 8004 by an electric fieldgenerated in the fluid 8006, as described above. The sensor reader 8008can sample the measurements obtained by the sensing region 8004 at oneor more different resolutions. In one embodiment, the sensor reader 8008can read the measurements of the sensing region 8004 at a resolution of8 bit. Alternatively, the resolution may be 12 bit, 16 bit, or anotherlarger resolution. The larger resolutions may be obtained by filteringnoise from the sampled measurements and/or by averaging multiplemeasurements.

The sensing region 8004 can operate as one or more LCR circuits that, inresponse to being excited by current provided to the LCR circuit,generate an electrical signal that represents impedance spectra of thesensing region 8004 during operational contact with the fluid 8006 overa measured spectral frequency range. The signal may be used to analyzethe impedance spectra and to determine one or more properties of thefluid as described herein.

The sensing region 8004 is directly connected with the sensor reader8008 in one embodiment. For example, the sensing region 8004 may becoupled with the sensor reader 8008 by one or more wireless connectionsor links. The signal that is output by the sensing region 8004 may becommunicated directly to the sensor reader 8008 without the signal beingconducted or otherwise communicated to another component and without thesignal being altered (e.g., filtered, amplified, digitized, conditioned,converted, or otherwise processed) by another component. Alternatively,the signal may be communicated from the sensing region 8004 to anothercomponent and modified or altered by the other component before beingconveyed to the sensor reader 8008.

The sensor reader 8008 may generate an output signal 8010 thatrepresents one or more characteristics of the industrial fluid 8006,such as an impedance spectrum, impedance spectra, an age of the fluid8006, a level or amount of contaminants in the fluid 8006, or the like.The output signal 8010 may be a digital signal. This output signal 8010may be communicated via one or more wired and/or wireless connections tothe controller described above, or to another location. In oneembodiment, the sensor assembly 8000 may have a digital address to allowcommunication between the sensor assembly 8000 and one or more otherdevices, such as the controller described above. The sensor reader 8008may provide digital data security to prevent one or more other devicesother than the controller or another reader from communicating with orcorrupting the data that is output by the sensor assembly 8000.

The sensor assembly 8000 includes an outer housing, or body, 8002. Thecircuitry of the sensor assembly 8000, including the sensor reader 8008and the sensing region 8008, may be within and/or attached directly tothe body 8002 such that the sensor reader 8008 and the sensing region8008 are proximate to each other and form a single device. In oneembodiment, these components are inside a single continuous orcontiguous body 8002, such as a single external housing. The body 8002may provide radio frequency (RF) shielding to the circuitry of thesensor assembly 8000 and may be able to provide dimensional and thermalstability, such as by protecting components within the body 8002 atelevated temperatures (e.g., temperatures up to 250 degrees Celsius).The body 8002 can provide environmental sealing of the components of thesensor assembly 8000. In one embodiment, the body 8002 is hermeticallysealed. Nonlimiting examples of materials that may be used to form thebody 8002 include stainless steel, aluminum, metal alloys, metal-ceramiccomposites, or metal dielectric composites.

The sensor assembly 8000 may be powered from a variety of sources. Asone example, the sensor assembly 8000 may include an internal battery asa power source. Alternatively, the sensor assembly 8000 can use ambientenergy harvesting to obtain electric power. In another example, thesensor assembly 8000 can operate with wirelessly supplied power, such asmay be provided through an inductive connection with a power source.

FIG. 81 illustrates a circuit diagram of one embodiment of the sensorassembly 8000 shown in FIG. 80. The sensor assembly 8000 can include avariable resistor R_(s) (or 8100) and a variable capacitor C_(s) (or8102), which can represent the sensing region 8004 (or the sensingregion 1938 shown in FIG. 20). An inductor L_(r) (or 8104) representsthe inductance of the wireless connection between the sensor reader 8010and the sensing region 8004. The inductor 8104 can be inductivelycoupled with an LCR circuit 8106 that represents the components thatprovide the resonant response of the sensor assembly 8000 to theelectric fields. The LCR circuit 8106 includes an inductor L_(p) (or8108), resistor R_(p) (or 8110), and capacitor C_(p) (or 8112) connectedin series with each other in a loop.

The circuit diagram of the sensor assembly 8000 shown in FIG. 81 may notallow for the resonance of the sensing region 8004 to be controlled, ortuned. For example, the sensor assembly 8000 shown in FIG. 81 mayresonate for a single frequency (dependent upon the condition of thefluid 8006, such as the age and/or level of contaminants in the fluid8006). In accordance with one or more embodiments of the subject matterdescribed herein, the resonance of the sensing region 8004 of the sensorassembly 8000 may be controlled (e.g., tuned) and be changed betweendifferent, predetermined frequencies. These frequencies may not bedictated by the fluid under examination, but may be selected by anoperator of the sensor assembly 8000.

The sensor reader 8008 may excite the sensing region 8004 throughmultiple different frequencies using active resonators in the circuitryof the sensor assembly 8000. Active resonators may include componentsthat are powered by a power source, such as a battery, energyharvesting, wireless power, or the like. Alternatively, the sensingregion 8004 may be excited using passive resonators in the circuitry ofthe sensor assembly 8000. Passive resonators may not be powered by apower source, but may be powered by inductive coupling or backscattercoupling with the sensor reader 8008. The excitation of the sensingassembly 8004 may be controlled by the sensor reader 8008 usingmulticarrier wideband excitation.

FIG. 82 illustrates a circuit diagram of the sensor assembly 800 shownin FIG. 80 in an embodiment where the resonance of the sensor assembly8000 may be controlled. The circuit diagram of the sensor assembly 8000may be similar or identical to the sensor circuit 2010 shown in FIG. 20,with the details of the tuning components 1942 (FIG. 20) shown in FIG.81. For example, the sensor assembly 8000 may include the resistor 8100,capacitor 8102, the LCR circuit 8106, and the inductor 8104, but alsomay include a variable capacitor C_(T) (or 8200) and a variable inductorL_(T) (or 8202) as the tuning components 1942 shown in FIG. 20.

While the resistance of the resistor 8100 and the capacitance of thecapacitor 8102 of the sensing region 8004 may change based on thecondition of the fluid 8006 (e.g., the age and/or level of contaminantsin the fluid 8006), the inductance of the inductor 8202 and/or thecapacitance of the capacitor 8200 may be varied (e.g., by the controlleror an operator) to change the resonant frequency of the sensing region8004. For example, the inductance and/or capacitance may be increased ordecreased to change which frequencies of electric field cause thecurrent conducted in the sensor assembly 8000 to resonate.

The tunable resonance of the sensor assembly 8000 allows the sensorassembly 8000 to examine the fluid 8006 to determine which of severaldifferent frequencies cause the sensor assembly 8000 to resonate. Incontrast to using several different sensor assemblies that each resonateat different frequencies, the sensor assembly 8000 may be a singlesensor with a single sensing region 8004 that can change whichfrequencies cause the sensing region 8004 to resonate. The controller ofthe sensing system can control the frequency at which the sensing region8004 resonates by changing the capacitance and/or the inductance of thevariable capacitor 8200 and inductor 8202.

The sensor assembly 8000 can operate as a multi-frequency, non-resonantsensor capable of operating at several different frequencies acrossdispersion profiles of different external contaminants and agingproducts (e.g., in the fluid 8006). The resonance of the sensor assembly8000 may be tuned to not resonate in response to excitation at one ormore frequencies. The electric fields with the resonant frequencies maybe harmonic resonant frequencies. Alternatively, the electric fieldswith the resonant frequencies may be non-harmonic resonant frequencies.The impedance of the fluid 8006 may change with increasing age, levelsof contaminants, and/or the presence of different contaminants in thefluid 8006. For example, in a first state (e.g., with the first staterepresenting a first capacitance of the variable capacitor 8200 and afirst inductance of the variable inductor 8202), the circuit of thesensor assembly 8000 may resonate at a first frequency while the sensingregion 8004 is at least partially submerged in the fluid underexamination. But, in a different, second state (e.g., with second staterepresenting a different, second capacitance of the variable capacitor8200 and/or a different, second inductance of the variable inductor8202), the circuit of the sensor assembly 8000 may not resonate at thesame first frequency while the sensing region 8004 is at least partiallysubmerged in the fluid under examination.

The sensor reader 8008 may control the frequencies at which the sensorassembly 8000 generates an electric field in the fluid underexamination. For example, the sensor reader 8008 may include anintegrated circuit that causes the sensor assembly 8000 to sweep throughseveral different frequencies of electric fields. The sensor reader 8008may sweep through the frequencies by changing the frequency of theelectric field in a continuous manner such that, during a frequencysweep, the frequency continually changes. The frequency can continuallychange by not being the same frequency at any two points in time andvarying between many different frequencies (e.g., more than twofrequencies) during the frequency sweep from a first frequency to adifferent, second frequency. Such a sensor reader 8008 can be referredto as a frequency-sweeping sensor reader 8008 or a frequency-sweepingintegrated circuit.

Optionally, the sensor reader 8008 may include an integrated circuitthat causes the sensor assembly 8000 to step through several differentfrequencies of electric fields. The sensor reader 8008 may step throughthe frequencies by changing the frequency of the electric field in anon-continuous manner. For example, the sensor reader 8008 can cause thesensing assembly 8000 to generate an electric field at a first frequencyfor a first period of time, then change to generating the electric fieldat a different, second frequency for a second period of time, and so on.The frequency can change in a step-wise manner by remaining at the samefrequency for each of the periods of time. These periods of time may besame or may be different. Such a sensor reader 8008 can be referred toas a frequency-stepping sensor reader 8008 or a frequency-steppingintegrated circuit. The sensor reader 8008 can excite the sensing region8004 through several frequencies using sliding window correlation forwide band measurements. The sliding window correlation is a techniquefor measurements of the frequency and phase characteristics of a rangeof signals that are related to a sensor device. This technique is usedto perform such measurements over a broad band of frequencies. Thecorrelation can be applied in order to measure response of the sensorassembly 8000 over a spectral range from 10 Hz to 10 GHz (or anotherfrequency range).

As described above, the spectral response of the sensing region 8004 inthe fluid of interest can represent characteristics of the fluid, suchas a level of degradation or age of the fluid and/or levels or amountsof external contaminants in the fluid. The sensor assembly 8000 canoperate in a multivariable mode by changing whether the sensing region8004 resonates or does not resonate at various frequencies in order toprovide measurements of multiple outputs from the sensing region 8004.Some outputs can represent the response of the sensing region 8004during time periods that the sensing region 8004 does not resonate inthe electric field generated in the fluid, while other outputs canrepresent the response of the sensing region 8004 during other timeperiods that the sensing region 8004 resonates in the electric fieldgenerated in the fluid. These outputs represent independent measurementsof changes in the fluid, and can be used to more accurately characterizethe state of the fluid. For example, the resonant and non-resonantresponses of the sensing assembly 8000 in different electric fields canbe measured in different fluids having different known ages anddifferent known levels of contaminants. These responses can be comparedto resonant and/or non-resonant responses of the sensing assembly 8000measured in a fluid under examination with an unknown age and/or levelof contaminants. This comparison can be used to determine or estimatethe age and/or level of contaminants in the fluid under examination,such as by determining which of the known responses more closely matchthe responses of the sensing assembly 8000 in the fluid underexamination than other known responses.

In one embodiment, the sensor assembly 8000 may be calibrated priorand/or during measurements of the fluid 8006. The controller (describedabove) may calibrate the sensor reader 8008 and/or the sensing region8004 based on ambient or external conditions to which the sensorassembly 8000 is exposed.

FIG. 83 illustrates operation of the sensor assembly 8000 at severaldifferent non-resonant frequencies according to one example. Ahorizontal axis 8300 represents different frequencies of the electricfield generated in the fluid by the sensor assembly 8000, a firstvertical axis 8302 represents different capacitances of the fluid 8006as measured by the sensor assembly 8000, and a second vertical axis 8304represents different resistances of the fluid 8006 as measured by thesensor assembly 8000.

The sensor assembly 8000 is tuned to not resonate in the electric fieldsof the different frequencies “Freq 1,” “Freq 2,” “Freq i,” and “Freq N”.The capacitances C (e.g., capacitances 8306, 8308, 8310, 8312) andresistances R (e.g., resistances 8314, 8316, 8318, 8320) of the fluid8006 were measured by the sensor assembly 8000 during exposure of theassembly 800 to the different non-resonant frequencies. As shown in FIG.83, the sensing region 8004 of the sensor assembly 8000 may measure arange of capacitances C and resistances R of the sensor that in contactwith fluid 8006 at several non-resonant frequencies of the sensorassembly 8000. The set or group of capacitances C and resistances Ratone or more of the non-resonant frequencies may vary over a range ofvalues, as shown in FIG. 83. For example, the capacitances 8306 andresistances 8314 for the frequency Freq 1 vary over a larger range thanthe capacitances 8310, 8312 and resistances 8318, 8320 for thefrequencies Freq i and Freq N.

FIG. 84 illustrates operation of the sensor assembly 8000 at severaldifferent resonant frequencies according to one example. A horizontalaxis 8400 represents frequencies of electric fields generated in thefluid by the sensor assembly 8000 and a vertical axis 8402 representsimpedance of the sensor as measured by the sensor assembly 8000 at thevarious frequencies. The sensor assembly 8000 generated electric fieldsof a range of frequencies by sweeping through different ranges offrequencies. For each of the range of frequencies that were sweptthrough by the sensor assembly 8000, real and imaginary impedance peaks8404, 8406 were measured by the sensor assembly 8000. These peaks 8404,8406 occur at frequencies to which the sensor assembly 8000 resonates.

The capacitances, resistances, and/or impedances measured by the sensorassembly 8000 while operating in a non-resonating mode (e.g., theexample of FIG. 83) and/or in a resonating mode (e.g., the example ofFIG. 84) can be used to determine the age and/or level of contaminantsin the fluid under examination. Different combinations of capacitances,resistances, and/or impedances for fluids having known ages and levelsof contaminants may be measured by the sensor assembly 8000 whileoperating in the non-resonating and/or resonating modes. Thesecapacitances, resistances, and/or impedances can then be compared tocapacitances, resistances, and/or impedances measured for fluids havingunknown ages and/or levels of contaminants using the sensor assembly8000 while operating in the non-resonating and/or resonating modes. Thecapacitances, resistances, and/or impedances associated with the knownfluids can be compared with the measured capacitances, resistances,and/or impedances of fluids under examination which have unknown agesand/or contaminants level to determine the ages and/or contaminantlevels of the fluids under examination. The ages and/or contaminantslevels of the fluids under examination may be measured on different timescales ranging from microseconds to days and to years.

FIG. 85 illustrates measured capacitances 8500, 8502, 8504, 8506, 8508,8510, 8512, 8514 for different levels of a contaminant in a fluid underexamination according to one example. Measurements were performed usingan IDE structure connected to an application specific integrated circuitavailable from Analog Devices (Model AD5933) that was the sensor reader8008. The measured capacitances 8500, 8502, 8504, 8506, 8508, 8510,8512, 8514 are shown alongside a horizontal axis 8516 representative offrequency (e.g., in units related to hertz) and a vertical axis 8518representative of capacitance measured by the sensor assembly 8000(e.g., in units of picoFarads). The sensor reader 8008 used afrequency-sweeping process to examine a range of frequencies of electricfields to measure the capacitances 8500, 8502, 8504, 8506, 8508, 8510,8512, 8514 shown in FIG. 85. The fluid under examination in FIG. 85 wasethanol and the contaminant in the ethanol was water. The capacitances8500, 8502, 8504, 8506, 8508, 8510, 8512, 8514 were measured fordifferent levels of water in ethanol. The table below lists the level(e.g., amount) of water for each of the capacitances the capacitances8500, 8502, 8504, 8506, 8508, 8510, 8512, 8514 that were measured.

Capacitances Level of Water in Ethanol (in milliliters) 8500 20 8502 108504 5 8506 4 8508 3 8510 2 8512 1 8514 0

FIG. 86 illustrates measured resistances 8600, 8602, 8604, 8606, 8608,8610, 8612, 8614 for different levels of the contaminant in the fluidunder examination according to the example of FIG. 85. The measuredresistances 8600, 8602, 8604, 8606, 8608, 8610, 8612, 8614 are shownalongside a horizontal axis 8616 representative of frequency (e.g., inunits related to hertz) and a vertical axis 8618 representative ofresistance measured by the sensor assembly 8000 (e.g., in units ofohms). The sensor reader 8008 used a frequency-sweeping process toexamine a range of frequencies of electric fields to measure theresistances 8600, 8602, 8604, 8606, 8608, 8610, 8612, 8614 shown in FIG.86. The fluid under examination in FIG. 86 was the same fluid with thecapacitances shown in FIG. 85. The table below lists the level (e.g.,amount) of water for each of the resistances in the resistances 8600,8602, 8604, 8606, 8608, 8610, 8612, 8614 that were measured.

Capacitances Level of Water in Ethanol (in milliliters) 8600 20 8602 108604 5 8606 4 8608 3 8610 2 8612 1 8614 0

In another demonstration, the application specific integrated circuitavailable from Analog Devices (Model AD5933) was used as the sensorreader 8008 and was connected to an IDE sensor structure coated with avapor-sensing film comprised of ligand-capped metal nanoparticles. ThisIDE sensor structure operated in a non-resonant mode because the sensordid not include an inductor in its circuit. Measurements were performedat multiple frequencies over the range from 1 kHz to 100 kHz uponperiodic exposure of the IDE sensor to three vapors at their twoconcentrations each. Vapor 1 was water vapor, vapor 2 was toluene vapor,and vapor 3 was ethyl acetate vapor. These vapors were used as modelvapors to demonstrate the applicability of the developed sensor system.The integrated circuit Analog Devices Model AD5933 provided severalanalog outputs measured from the sensor as a function of frequency.Nonlimiting examples of these outputs include the real part of impedance(Zre), the imaginary part of impedance (Zim), magnitude, phase,equivalent sensor capacitance (Cp), and equivalent sensor resistance(Rp).

FIG. 87 depicts an example of sensor response Zre as a function ofexperimental time at three frequencies such as 10 kHz, 35 kHz, and 100kHz. During the experiment, the sensor assembly 8000 was first exposedto vapor 1 at a relatively small concentration followed by sensorexposure to a higher concentration of vapor 1. Next, the sensor assembly8000 was exposed to vapor 2 at a relatively small concentration followedby sensor exposure to a higher concentration of vapor 2. Finally, thesensor assembly 8000 was exposed to vapor 3 at a relatively smallconcentration followed by sensor exposure to a higher concentration ofvapor 3. All exposures of the sensor assembly 8000 to vapors wereperformed with 60-second durations. The sensor assembly 8000 was exposedto a blank carrier gas (dry air) between exposures to vapors. Each vaporproduced a different response pattern at these three displayedfrequencies. For example, vapor 1 produced a relatively small positiveresponse at 10 kHz in relation to other two vapors. At 35 kHz, vapor 1produced also a relatively small response in relation to other twovapors but with the negative direction of the response. At 100 kHz,vapor 1 produced a response that was comparable with the responses toother two vapors. Response to vapor 2 was slightly larger than responseto vapor 3 at 10 kHz and at 35 kHz and was comparable to response tovapor 3 at 100 kHz. These results demonstrate that measurements ofoutputs at different frequencies from a non-resonant sensor assembly8000 using the application specific integrated circuit provided desireddiverse responses which are needed for differentiation of differentvapors.

FIG. 88 depicts a scores plot of a developed PCA model based on thesensor response results presented in FIG. 87. This plot illustrates thatthe sensor assembly 8000 was able to differentiate between the threevapors. The different directions of the sensor responses to vapors 1, 2,and 3 were indicated with arrows in FIG. 88.

FIG. 89 depicts an example of sensor responses Zre (the real part ofimpedance), Zim (the imaginary part of impedance), Cp (equivalent sensorcapacitance), and Rp (equivalent sensor resistance), all measured at asingle frequency of 100 kHz and using the sensor assembly 8000 andsensor reader described in relation to FIG. 87. Same as in FIG. 87,these measurements were performed by exposing the same sensor assembly8000 to the same three vapors. Unlike FIG. 87, the measurements wereperformed with two replicates. These results demonstrate thatmeasurements of different outputs from a sensor assembly 8000 using theapplication specific integrated circuit provided desired diverseresponses Zre, Zim, Cp, and Rp as measured at a single frequency. Suchmeasured response diversity is needed for differentiation of differentvapors.

Measurements of another sensor assembly 8000 were performed uponexcitation of the sensor assembly at multiple frequencies. The sensorreader 8008 was sweeping through the frequencies by changing thefrequency of the electric field in a continuous manner. The sensorassembly 8000 had an IDE structure coated with a vapor-sensing filmcomprised of ligand-capped metal nanoparticles and one inductor. Thepresence of one inductor produced a resonant circuit with the measuredparameters of the circuit Fp, Fz, Zp, F1, F2, Z1, and Z2 as described inFIG. 23. The sensor assembly 8000 was periodically exposed to fourvapors at their four concentrations each. The four vapors 1-4 werewater, methyl salicylate, toluene, and acetone. These vapors were usedas model vapors to demonstrate the applicability of the developed sensorsystem. Collected responses Fp, Fz, Zp, F1, F2, Z1, and Z2 were analyzedusing PCA.

FIG. 90 illustrates plots of the first four principal components (PCs)of the developed PCA model as a function of experimental time duringexposures to vapors that show the distinct recognition pattern up to PC4between four model vapors at their four concentration levels. Theseresults are of significant importance for the ability of a single sensorassembly 8000 to differentiate between multiple vapors.

Control of detection sensitivity of impedance measurements has beendemonstrated in the present disclosure in the resonant and non-resonant(conventional) detection modes. When detection sensitivity was comparedbetween resonant and conventional impedance measurements, sensitivityenhancement of up to ˜74 fold was achieved for resonant vs. conventionalimpedance measurements.

FIG. 91 depicts results of dynamic measurements of a solution with asensor assembly 8000 over time when the changes in the solutionproperties were measured using resonant impedance (two lines and anarrow 1 illustrating response direction for the lowest frequencyresonator) and conventional impedance (two lines and an arrow 2illustrating response direction). Resonant impedance measurements wereperformed with four resonators. The enhancement of the measurementsensitivity using resonant impedance over conventional impedance wascalculated as the ratio of response sensitivity measured using aparticular resonator (length of arrow 1 in FIG. 91) to the responsesensitivity measured using conventional impedance at the same frequencyrange as the resonator (length of arrow 2 in FIG. 91). In FIG. 91, theratio between sensitivity of the resonator that operated at the smallestresonant frequency and the sensitivity using conventional impedance was˜74 (the ratio of the length of arrow 1 to the length of arrow 2). Thisvalue indicated the enhancement of the measurement sensitivity usingresonant impedance over conventional impedance. The sensor assembly usedin this experiment was an interdigital electrode structure coated with adielectric protective layer. The layer thickness and the geometry of theelectrode structure provided the control of the enhancement of themeasurement sensitivity using resonant impedance over conventionalimpedance.

FIG. 92 depicts results of dynamic measurements of a solution over timewhen the changes in the solution properties were measured using resonantimpedance (two lines and an arrow 1 illustrating response direction forthe lowest frequency resonator) and conventional impedance (two linesand an arrow 2 illustrating response direction). This sensor assemblydid not have a protective dielectric layer. In FIG. 92, the ratiobetween sensitivity of the resonator that operated at the smallestresonant frequency and the sensitivity using conventional impedance wasapproximately a unity (the ratio of the length of arrow 1 to the lengthof arrow 2). This value indicated no enhancement of the measurementsensitivity using resonant impedance over conventional impedance whenthe sensor had the described configuration.

In another demonstration, the application specific integrated circuitavailable from AMS (Model SL900A) was used as the sensor reader 8008 andwas connected to a single IDE sensor structure coated with avapor-sensing film comprised of ligand-capped metal nanoparticles.Alternatively, it was connected to two IDE sensor structures, eachcoated with a vapor-sensing film comprised of ligand-capped metalnanoparticles. This sensor system operated in a non-resonant modebecause it did not include an inductor in its circuit. Alternatively,this sensor system may operate when the connected sensor or sensorsinclude an inductor. The sensor reader measured capacitance andresistance of the sensor or sensors connected to the two inputs of thesensor reader. Measurements were performed at two frequencies, onefrequency for capacitance measurements and another frequency forresistance measurements. Measurements of capacitance and for resistanceat different frequencies allows enhancement of selectivity of theresponse of the sensor system to different vapors or fluids. The sensorsystem was periodically exposed to four vapors at their twoconcentrations each. Vapor 1 was water vapor, vapor 2 was isopropylalcohol vapor, vapor 3 was methanol vapor, and vapor 4 was toluenevapor. These vapors were used as model vapors to demonstrate theapplicability of the developed sensor system. The integrated circuit AMSModel SL900A provided two digital outputs measured from the connectedsensor or sensors.

FIG. 93 illustrates capacitance response and resistance response of thesensor assembly under examination of a fluid such as vapors as measuredby the sensor assembly 8000 in accordance with one example. The sensorsystem shows the responses in counts because the original measuredvalues of capacitance and resistance are digitized in the sensor readerAMS Model SL900A for wireless or wired transmission to the end-user. Thesensor assembly 8000 measured the capacitances and resistances inambient air.

The term “fluids” can include gases, vapors, liquids, and solids andtheir combinations forming multiphase compositions. Non-limitingexamples of multiphase compositions include emulsions such as oil/wateremulsions, food emulsions such as salad dressings oil-in-wateremulsions, colloids such as solutions that have particles distributedthroughout the solution, food colloids, food colloids such as icescream, jam, mayonnaise, solid foams such as bread, cake. Fluid can alsoinclude a food product that has been gone through mechanical re-forming.Alternatively, a fluid may not include a solid.

The term “analyte” can include a substance or chemical constituent thatis the subject of a chemical analysis. Examples of analytes include, butare not limited to, water, fuel, hydrogen, carbon monoxide, carbondioxide, methane, ethane, ethylene, acetylene, acids, metals, agingproducts, or any combination thereof. In certain embodiments, thesensing materials of the present disclosure may be configured to detectanalytes.

The term “multivariable sensor” can refer to a single sensor capable ofproducing multiple response signals that are not substantiallycorrelated with each other and where these individual response signalsfrom the multivariable sensor are further analyzed using multivariateanalysis tools to construct response patterns of sensor exposure todifferent analytes at different concentrations. In one embodiment,multivariable or multivariate signal transduction is performed on themultiple response signals using multivariate analysis tools to constructa multivariable sensor response pattern. In certain embodiments, themultiple response signals comprise a change in a capacitance and achange in a resistance of a sensing material disposed on a multivariablesensor when exposed to an analyte. In other embodiments, the multipleresponse signals comprise a change in a capacitance, a change in aresistance, a change in an inductance, or any combination thereof.

The term “multivariate analysis” can refer to a mathematical procedurethat is used to analyze more than one variable from the sensor responseand to provide the information about the type of at least oneenvironmental parameter from the measured sensor parameters and/or toquantitative information about the level of at least one environmentalparameter from the measured sensor parameters. Non-limiting examples ofmultivariate analysis tools include canonical correlation analysis,regression analysis, nonlinear regression analysis, principal componentsanalysis, discriminate function analysis, multidimensional scaling,linear discriminate analysis, logistic regression, or neural networkanalysis.

The term “spectral parameters” can refer to measurable variables of thesensor response. The sensor response is the impedance spectrum of theLCR sensor. In addition to measuring the impedance spectrum in the formof Z-parameters, S-parameters, and other parameters, the impedancespectrum (for example, both real and imaginary parts) may be analyzedsimultaneously using various parameters for analysis, such as, thefrequency of the maximum of the real part of the impedance (Fp), themagnitude of the real part of the impedance (Zp), the resonant frequencyof the imaginary part of the impedance (F1), the anti-resonant frequencyof the imaginary part of the impedance (F2), signal magnitude (Z1) atthe resonant frequency of the imaginary part of the impedance (F1),signal magnitude (Z2) at the anti-resonant frequency of the imaginarypart of the impedance (F2), and zero-reactance frequency (Fz, frequencyat which the imaginary portion of impedance is zero). Other spectralparameters may be simultaneously measured using the entire impedancespectra, for example, quality factor of resonance, phase angle, andmagnitude of impedance. Collectively, “spectral parameters” calculatedfrom the impedance spectra may also be called “features” or“descriptors.” The appropriate selection of features is performed fromall potential features that can be calculated from spectra.

As used herein, the term “sensing materials and sensing films” caninclude, but is not limited to, materials deposited onto an electronicsmodule of a transducer, such as LCR circuit components to perform thefunction of predictably and reproducibly affecting the impedance sensorresponse upon interaction with the environment. In order to prevent thematerial in the sensor film from leaching into the liquid environment,the sensing materials are attached to the sensor surface using standardtechniques, such as covalent bonding, electrostatic bonding, and otherstandard techniques known to those of ordinary skill in the art.

As used herein, an element or step recited in the singular and proceededwith the word “a” or “an” should be understood as not excluding pluralof said elements or steps, unless such exclusion is explicitly stated.Furthermore, references to “one embodiment” of the presently describedinventive subject matter are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features. Moreover, unless explicitly stated to the contrary,embodiments “comprising,” “including,” or “having” (or like terms) anelement, which has a particular property or a plurality of elements witha particular property, may include additional such elements that do nothave the particular property.

As used herein, terms such as “system,” “module,” or “controller” mayinclude hardware and/or software that operate(s) to perform one or morefunctions. For example, a system, module, or controller may include acomputer processor or other logic-based device that performs operationsbased on instructions stored on a tangible and non-transitory computerreadable storage medium, such as a computer memory. Alternatively, asystem, module, or controller may include a hard-wired device thatperforms operations based on hard-wired logic of the device. Thesystems, modules, and controllers shown in the Figures may represent thehardware that operates based on software or hardwired instructions, thesoftware that directs hardware to perform the operations, or acombination thereof

As used herein, terms such as “operably connected,” “operativelyconnected,” “operably coupled,” “operatively coupled” and the likeindicate that two or more components are connected in a manner thatenables or allows at least one of the components to carry out adesignated function. For example, when two or more components areoperably connected, one or more connections (electrical and/or wirelessconnections) may exist that allow the components to communicate witheach other, that allow one component to control another component, thatallow each component to control the other component, and/or that enableat least one of the components to operate in a designated manner.

It is to be understood that the subject matter described herein is notlimited in its application to the details of construction and thearrangement of elements set forth in the description herein orillustrated in the drawings hereof. The subject matter described hereinis capable of other embodiments and of being practiced or of beingcarried out in various ways. Also, it is to be understood that thephraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including,” “comprising,” or “having” and variations thereof herein ismeant to encompass the items listed thereafter and equivalents thereofas well as additional items.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (and/or examples thereof) may be used in combination witheach other. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the presentlydescribed subject matter without departing from its scope. While thedimensions, types of materials and coatings described herein areintended to define the parameters of the disclosed subject matter, theyare by no means limiting and are exemplary embodiments. Many otherembodiments will be apparent to one of ordinary skill in the art uponreviewing the above description. The scope of the inventive subjectmatter should, therefore, be determined with reference to the appendedclaims, along with the full scope of equivalents to which such claimsare entitled. In the appended claims, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Moreover, in the following claims, the terms“first,” “second,” and “third,” etc. are used merely as labels, and arenot intended to impose numerical requirements on their objects. Further,the limitations of the following claims are not written inmeans-plus-function format and are not intended to be interpreted basedon 35 U.S.C. §112(f), unless and until such claim limitations expresslyuse the phrase “means for” followed by a statement of function void offurther structure.

This written description uses examples to disclose several embodimentsof the inventive subject matter, and also to enable one of ordinaryskill in the art to practice the embodiments of inventive subjectmatter, including making and using any devices or systems and performingany incorporated methods. The patentable scope of the inventive subjectmatter is defined by the claims, and may include other examples thatoccur to one of ordinary skill in the art. Such other examples areintended to be within the scope of the claims if they have structuralelements that do not differ from the literal language of the claims, orif they include equivalent structural elements with insubstantialdifferences from the literal languages of the claims.

What is claimed is:
 1. A sensor system comprising: a multi-frequencysensor assembly including a single sensor body housing with a sensingregion circuit and a sensor reader disposed in the sensor body, thesensor body configured to be in operational contact with a fluid, thesensing region circuit configured to generate different electric fieldshaving different frequencies in the fluid, the sensor reader includingone or more processors configured to examine one or more impedanceresponses of the sensing region circuit at different frequencies and todetermine one or more properties of the fluid based on the one or moreimpedance responses that are examined.
 2. The sensor system of claim 1,wherein the sensor reader is configured to acquire measurements of theone or more impedance responses from the sensing region circuit at aresolution of one or more of 8 bit, 12 bit, or 16 bit.
 3. The sensorsystem of claim 1, wherein the sensor reader is configured to acquiremeasurements of the one or more properties of the fluid at a resolutiongreater than 16 bit by one or more of filtering or averaging themeasurements.
 4. The sensor system of claim 1, wherein the single sensorbody housing is configured to protect the sensing region circuit and thesensor reader from damage caused by temperatures up to 250 degreesCelsius.
 5. The sensor system of claim 1, wherein the single sensor bodyhousing is configured to operate the sensing region circuit and thesensor reader at temperatures up to 250 degrees Celsius.
 6. A sensorsystem comprising: a multi-frequency sensor assembly including a singlesensor body housing with a sensing region circuit and a sensor readerdisposed in the sensor body, the sensor body configured to be inoperational contact with an industrial fluid, the sensing region circuitconfigured to generate different electric fields having differentfrequencies in the fluid, the sensor reader including one or moreprocessors configured to examine one or more impedance spectra of thesensing region circuit and to determine one or more properties of thefluid based on the one or more impedance spectra that are examined. 7.The sensor system of claim 6, wherein the sensor reader is configured todetermine one or more of an amount of contaminants in the fluid or anage of the fluid as the one or more properties of the fluid based on theone or more impedance spectra that are examined.
 8. The sensor system ofclaim 6, wherein the sensing region circuit is a non-resonant circuitfor the frequencies of the electric fields generated by the sensingregion circuit in the fluid.
 9. The sensor system of claim 6, whereinthe sensing region circuit is a resonant circuit for the frequencies ofthe electric fields generated by the sensing region circuit in thefluid.
 10. The sensor system of claim 6, wherein the sensing regioncircuit is configured to generate the electric fields with the resonantfrequencies being non-harmonic resonant frequencies.
 11. The sensorsystem of claim 6, wherein the sensing region circuit is configured togenerate the frequencies by sweeping through the frequencies.
 12. Thesensor system of claim 6, wherein the sensing region circuit isconfigured to generate the frequencies by stepping through thefrequencies such that discrete frequencies are generated at differenttimes for different, non-zero periods of time.
 13. The sensor system ofclaim 6, wherein the sensing region circuit includes aninductor-capacitor-resistor (LCR) resonator.
 14. The sensor system ofclaim 6, wherein the sensor body housing is hermetically sealed from thefluid.
 15. The sensor system of claim 6, wherein the sensor body housingis configured to provide radio frequency shielding to the sensing regioncircuit.
 16. The sensor system of claim 6, wherein the sensor reader isconfigured to communicate a digital output signal to an externalcontroller that represents at least one of the impedance spectra of thesensing region circuit or the properties of the fluid.
 17. The sensorsystem of claim 16, wherein the sensor reader is configured tocommunicate the digital output signal as one or more of a wirelesssignal or a signal communicated to the external controller via a wiredconnection.
 18. The sensor system of claim 6, wherein the sensor readerhas a digital address for communication with an external controller. 19.The sensor system of claim 6, wherein the sensor reader is configured toprovide digital data security for communication between the sensorreader and one or more external controllers.
 20. The sensor system ofclaim 6, wherein the sensor assembly is configured to be powered viaambient energy harvesting.
 21. The sensor system of claim 6, wherein thesensor assembly is configured to be powered via wirelessly suppliedpower.
 22. The sensor system of claim 6, wherein the sensor reader andthe sensing region are configured to be calibrated for externalconditions by one or more external controllers.
 23. The sensor system ofclaim 6, wherein the sensor reader is configured to excite the sensingregion using multi-frequency excitation with a sliding window correlatorfor wide band measurements, and wherein the sensing region is configuredto measure response of the sensor assembly over a spectral range from 10Hz to 10 GHz.
 24. The sensor system of claim 6, wherein the sensorreader is configured to excite the sensing region using multi-frequencyexcitation via one or more resonators.
 25. The sensor system of claim24, wherein the one or more resonators are one or more activeresonators.
 26. The sensor system of claim 24, wherein the one or moreresonators are one or more passive resonators.
 27. The sensor system ofclaim 6, wherein the sensor reader is configured to excite the sensingregion using multicarrier wideband excitation.